Do tariff reductions affect the wagesof workers in protected industries?Evidence from the Canada-U.S. FreeTrade Agreement

James Townsend Department of Economics,University of Winnipeg

Abstract. In this paper, I use Canadian micro-data on individual workers to investigatethe effect on wages of the tariff reductions mandated by the Canada-U.S. Free TradeAgreement (CUSFTA). The literature on industry wage premia has revealed that theindustry of employment is an important determinant of a worker’s wage. My findingsindicate that relative wages fell in those industries that faced the deepest tariff cuts. Thiseffect was experienced regardless of whether or not workers belonged to a union, suggestingthat CUSFTA reduced the returns to industry-specific human capital for those workersin the mostly heavily affected industries. JEL classification: F16, F14

Est-ce que les reductions de tarifs douaniers affectent les salaires des travailleurs dans lesindustries protegees? Impact de l’Accord de libre echange Canada-Etats-Unis. Dans ce texte,l’auteur utilise des micro donnees canadiennes pour etudier le rapport entre les niveauxde salaires et les reductions de tarifs douaniers engendrees par l’accord de libre echangeCanada US. La litterature sur les primes salariales suggere que la structure industriellede l’emploi est un facteur determinant dans la determination des salaires des employes.Les resultats montrent que les salaires relatifs tombent dans les secteurs industriels ou lesreductions de tarifs sont les plus importantes. Cet impact est enregistre que les employessoient syndiques ou non. Voila qui suggere que l’Accord de libre-echange reduit les ren-dements sur le capital humain qui est specifique a une industrie pour les travailleurs desindustries les plus fortement affectees.

1. Introduction

In 1988, Canada and the United States signed the Canada-U.S. Free Trade Agree-ment (CUSFTA), which came into effect on 1 January 1989 and required the

I would like to thank David Green, Brian Copeland, Thomas Lemieux, and Keith Head fortheir helpful comments.

Canadian Journal of Economics / Revue canadienne d’Economique, Vol. 40, No. 1February/fevrier 2007. Printed in Canada / Imprime au Canada

0008-4085 / 07 / 69–92 / C© Canadian Economics Association

70 J. Townsend

phasing out of tariffs on goods traded between the two countries over a ten yearperiod. For Canada, CUSFTA was a major policy initiative, involving deeperintegration with its most important trading partner. In 1988, the year beforeCUSFTA came into effect, trade with the United States accounted for 72.8%of Canadian exports and 65.6% of Canadian imports. The agreement was vehe-mently opposed by organized labour, which argued that CUSFTA would leadto Canadian job losses resulting from closure of U.S. branch plants. Proponentsargued that CUSFTA would improve efficiency in Canadian manufacturing, asimproved access to the large U.S. market would allow plants to exploit economiesof scale.

CUSFTA arguably provides a natural experiment with which to evaluate theeffects of trade liberalization on labour market outcomes. As Trefler (2004) notes,the agreement was not part of a package of broader economic reforms, as has beenthe case with tariff reductions in developing countries. CUSFTA also resulted insubstantial variation in tariffs, as tariffs were eliminated in both high and lowtariff industries. Bilateral tariffs were decreasing in the period prior to CUSFTA(1979–87), as both countries honoured their commitments from the Tokyo roundof the General Agreement on Trade and Tariffs (GATT) negotiations. However,the reductions were small and were applied such that those industries with hightariffs at the beginning of the period continued to have high tariffs at the end ofthe period, leaving the relative tariff structure unchanged.1

In this paper, I use a collection of microdata sets with detailed informationon the human capital characteristics and industry of affiliation of individualworkers to examine the relationship between the wages of Canadian workers andthe tariff protection against American imports afforded to the industry in whichthey work. I follow the methodology developed by Gaston and Trefler (1995)and examine the relationship between interindustry wage differentials and tradepolicy. Using data on U.S. workers, Katz and Summers (1989) demonstrate theexistence of substantial wage differences across industries, even after controllingfor differences in the observable characteristics of workers. Once occupation, sex,and region are controlled for, inclusion of controls for educational attainmenthave little effect on the magnitude of the estimated premia, suggesting that theindustry premia are the result of rents paid to workers rather than differences inthe unobserved skills of workers. The interindustry wage differentials have alsobeen shown to be persistent over time, which suggests that they represent rentsrather than the outcome of transitory differences in labour market conditionsacross industries.

Using data on U.S. workers from the 1984 Current Population Survey (CPS),Gaston and Trefler (1995) examine the extent to which the premia are related totariffs and non-tariff trade barriers. Given that organized labour has traditionallyresisted liberalization, Gaston and Trefler examine the union and the non-union

1 Based on 2-digit industry categories, the correlation between the 1981 and 1988 Canadian tariffagainst American imports was .96.

Do tariff reductions affect wages? 71

sectors separately. They find no relationship between industry tariffs and wagepremia in the non-union sector. They find a negative relationship between tariffsand the wage premia in the union sector, which is robust to estimation wheninstrumental variables are introduced to control for possible endogeneity betweenthe wage premia and the applicable tariff. This finding is puzzling, given the stanceof unions towards trade liberalization. A related paper by Goldberg and Pavcnik(2005) examines the relationship between industry wage premia and tariffs forworkers in Columbia. Goldberg and Pavcnik use panel data with informationon the wages and characteristics of Columbian workers that spans the period1984–98 and take advantage of major liberalization initiatives that occurred thisperiod. Using the variation of tariffs over time within industries, Goldberg andPavcnik find a positive correlation between the tariff of industry and the wagepremium paid to workers within the industry. This suggests that reducing tariffshas a negative effect on workers, either by reducing the rents available to them orby temporarily decreasing wages as workers are displaced from the industry.

My work is also closely related to the empirical literature examining the ef-fects of CUSFTA on the earnings and employment of Canadian workers in theaffected industries. These studies have used industry averages on earnings andemployment, either for all workers or for production and non-production work-ers separately. Production and non-production workers are used as proxies forunskilled and skilled workers, respectively. Gaston and Trefler (1997) find norelationship between between the average earnings of all workers in an indus-try and the tariffs applicable to the industry. Similarly, Beaulieu (2000) findsno relationship between average earnings and tariffs for either non-productionor production workers. In contrast, Trefler (2004) finds a negative relationshipbetween tariffs and the earnings of production workers, which suggests that CUS-FTA improved the earnings of workers in industries facing the largest tariff cuts.All three studies find that the industries facing the largest tariffs cuts experiencedemployment losses. Both Trefler (2004) and Beaulieu (2000) find that job losseswere concentrated among production workers.

By working with microdata and using hourly wages, I make several contri-butions to our understanding of how the CUSFTA tariff cuts affected earnings.First, by using hourly earnings and controlling for individual characteristics, Iam able to isolate the effect of CUSFTA on the wage rate, which is a measure ofthe price of labour. Previous studies have worked with average weekly earningsfor broad groups of workers. Changes in weekly earnings may come from a com-bination of price changes, changes in the composition of workers forming thegroup, and changes in the number of hours worked per week. Second, I am ableto compare the response in the union and non-union sectors, which may haveimportant implications for understanding the political economy of trade policy.My results indicate that the CUSFTA cuts resulted in a decline in the wages ofthose workers in sectors facing the largest cuts relative to the wages of the work-ers in sectors that already had low tariffs prior to CUSFTA. This result holdsfor both the union and the non-union sector. Wages in the union sector are also

72 J. Townsend

found to be responsive to changes in the industry-specific real exchange rate andto other sectoral shocks; no similar response is found in the non-union sector.

2. Empirical framework

Industry premia measure the difference in wages between workers who are obser-vationally equivalent (i.e., have the same vector of human capital characteristics)except for the industry in which they work. The premium for a single industry ismeaningful only as a comparison with a reference point or group. In a regressionframework, this involves either choosing an industry as the reference group, orcalculating the mean earnings across all industries and expressing the premiumfor each industry in terms of how the wages in that industry, conditional on acommon set of worker characteristics, deviate from the mean. In what follows, Ireport the industry premia as deviations from the annual mean, which is calcu-lated giving each industry equal weight.

The policy variables of interest are the own-industry American and Canadiantariffs. The Canadian tariff provides a measure of the protection given toCanadian industries against American imports. If this protection is beneficialto firms in the receiving industry and if workers are able to share in these ben-efits, then there will be a positive relationship between the Canadian tariff andthe relative wages of workers employed in that industry. The American tariff is ameasure of the barriers to exporting goods to the large U.S. market. Canadianfirms were expected to benefit from improved access to the American market. Ifworkers are able to share in these benefits, there will be a negative relationshipbetween the American tariff and the wage. In principle, tariff changes in other in-dustries could result in substitution effects. Following the literature, I ignore suchsubstitution effects. This is roughly equivalent to assuming that cross-elasticitiesbetween American and Canadian goods in the same industry are much largerthan the cross-elasticities between goods in different industries. Trade liberaliza-tion may also have had a common effect on wages across industries, throughgeneral equilibrium mechanisms. Such effects may have altered the relative re-turns to certain characteristics across all industries. Identification of such effectswould involve relating the appropriate returns to characteristics to a summarymeasure of the agreement. This issue is not addressed in this paper, as it is notclear what the appropriate statistic is to capture the general equilibrium effectof CUSFTA on the wage rate. Beaulieu (2000) considers the average tariff ratefor this purpose. He does not find a relationship between the average wages forskilled and unskilled labour and this measure.

In 1994 CUSFTA was replaced by the North American Free Trade Agreement(NAFTA), which expanded the free trade zone to include Mexico. Reductionsin bilateral tariffs between Canada and the United States were still governed bythe timetable laid out in CUSFTA, while bilateral tariffs with Mexico were to bephased out over a fourteen-year period. As with previous studies of CUSFTA,

Do tariff reductions affect wages? 73

I ignore the provisions of NAFTA. There are two arguments in favour of ignor-ing Mexico’s inclusion into the free trade zone. First, while the bilateral tariffreductions between Canada and the United States were complete in 1998, thereductions between Mexico and Canada were still in the early stages. Second,compared with the United States, Mexico accounted for only a tiny fraction ofCanada’s trade volume over the study period. For example, in 1998 the UnitedStates accounted for 85% of Canadian exports and 68.2% of Canadian imports.The same figures for Mexico were 0.5% and 2.6%, respectively.2

The empirical strategy employed in this paper is similar to that used in Gastonand Trefler (1995) and Goldberg and Pavcnik (2005) and draws upon the literaturein labour economics on interindustry wage premia. Let the wage, wijt, of individuali working in industry j at time t be determined by the process

log(wi jt) = Xitβt + Djtλ j t + εi j t, (1)

where Xit is a vector of standard human-capital characteristics specific to in-dividual i, and Djt is a vector of indicator variables in which the jth elementcorresponds to industry j. λjt is the wage premium associated with industry i attime t. The first term reflects the extent to which an individual’s wage can be ex-plained by his or her own observable characteristics, while the second term is theportion of the individual’s wage that can be accounted for by the industry of affil-iation. Wages of an individual with characteristics Xit employed in industry j maychange over time either because the returns to characteristics have changed on aneconomy-wide basis (i.e., βt �= βt+1) or because the industry-specific componentof the wage has changed (i.e., λ j t �= λ j t+1).

To incorporate tariff policy into (1), I assume that the wage premia, λjt aredetermined according to the process

λ j t = µ j + Ytα + Zjtδ + Tjtγ + ν j t, (2)

where Yt is a set of year dummies to control for common cross-industry businesscycle effects and other common shocks across industries, Zjt is a set of controlsfor industry specific changes in labour demand and supply conditions, Tjt is avector of trade policy parameters, µ j is an industry-specific fixed-effect, andν j t is an industry-specific shock. The parameter of interest is the tariff effect,γ . Industry fixed-effects are included to allow the industry premia to dependon unobserved features of industries such as workplace conditions that are notdirectly influenced by trade policy and that have remained relatively constantover time. Identification of the tariff effect is based on the extent to which tariffsand other industry-level variables can account for changes in the relative wagesbetween industries over time. Variation in the wage rate between industries is the

2 These figures were calculated by the author using data from the Strategis Web site(http://strategis.gc.ca) maintained by Industry Canada.

74 J. Townsend

result of a combination of industry fixed-effects, observable changes in tariffs andother variables, and unobserved shocks.

Estimates of the tariff effect are established through a two-step process. In thefirst step, equation (1) is estimated using the data from the labour surveys. Theestimates of the industry-year effects, λ j t, are used as the dependent variable inestimating equation (2). Since the dependent variable is estimated, equation (2)is estimated using weighted least squares, with the weights equal to the inverse ofthe standard error of the estimates of λ j t. The two-stage methodology is used toobtain the correct estimates of the standard errors of the estimated parametersin equation (2) – one could substitute equation (2) into equation (1) and obtainestimates of the desired parameters in a single step. However, obtaining correctestimates of the standard errors would require taking into account the dependenceof the error terms across individuals in the same industry in the same year, asrepresented by the common stochastic term ν jt.

In the first stage, the regressor Xit consists of characteristics commonly usedin wage equations; in particular, an indicator for gender is included, along withcategorical variables containing information on each individual’s level of educa-tional attainment, age, and years of job tenure at the current job.3 In addition,indicators for the province of habitation are included to control for regional dif-ferences in labour markets. The coefficients on these characteristics are estimatedseparately for the union and non-union sector. An individual is included in theunion sector if he or she is a member of a union at the current job. The wagepremia are estimated for all industries in each year, using the restriction that thepremia sum to zero for each year. In this representation, the wage premium ofindustry i indicates how the wage for a given worker in that industry comparesto the average wage across all industries for workers with the same set of individ-ual characteristics. Standard errors for the estimates of the industry premia arecalculated exactly using constrained least squares.

In the second-stage regression, explanatory variables consist of the contempo-raneous Canadian and American tariffs applicable to the industry, the log of totalAmerican employment in the same industry, the industry-specific real exchangerate, an industry fixed effect, and a common year effect. The industry-specific realexchange rate controls for changes in the terms of trade arising from the appreci-ation and devaluation of the Canadian dollar. The American employment effectis included to control for shocks to the industry stemming from either techno-logical changes or increased exposure to competition from firms outside the twocountries. After 1987 changes in the tariffs applied to goods produced by coun-tries outside CUSFTA were mostly governed by the Uruquay round of GATT; assignatories to this agreement, Canada and the United States were making similarreductions to tariffs applying to the goods of third-party countries.

Either the level of tariffs or the rate at which they were reduced may have beenendogenous. In section 4, I show that that low-wage industries in Canada tended

3 Detailed information on the categories that were used is provided in section 3.

Do tariff reductions affect wages? 75

to have higher rates of protection prior to CUSFTA. Workers in these industriesare more likely to be female and less likely to be a member of a union. This findingis consistent with a model of political economy like the one considered in Gastonand Trefler (1995), where low-wage industries are successful in lobbying for hightariffs. As long as the industry characteristics associated with whether or not anindustry is a ‘low’-wage industry remain constant over time, the use of panel datawith the inclusion of fixed-effects will address this problem, as the tariff effect isidentified using within-industry variation rather than cross-sectional variation.Goldberg and Pavcnik (2005) consider the possibility of endogeneity arising fromdynamic political economy considerations. In particular, they argue that policy-makers may have chosen different tariff cuts for industries with different growthrates. The nature of the CUSFTA cuts would have limited this kind of discretionon the part of policymakers, as the agreement required that all tariffs be phasedout within 10 years. However, it is possible that CUSFTA negotiators agreed tophase out tariffs more slowly in those industries with the slowest wage growth.In this case, a possible instrumenting strategy, suggested by Beaulieu (2000), isto take the 1988 tariffs and create instrumental variables by applying a commonphase-out period to all industries.

3. Data

My labour data are drawn from a collection of cross-sectional and longitudinaldata sets that span the period 1981–98. In particular, I use the 1981 Survey ofWork History (SWH), the 1984 Survey of Union Membership (SUM), the 1986–7Labour Market Activity Survey (LMAS), the 1988–90 LMAS, the 1995 Survey ofWork Arrangements (SWA), and the 1997 and 1998 Labour Force Survey (LFS).The year of each survey corresponds to the year for which the questions actuallyapply. All surveys are either from the LFS or supplements to the LFS and arecomparable in design and construction. These data sets were chosen because theycontain detailed information on each worker’s industry of affiliation, union statusand hourly wage.4 Although the Labour Force Survey has been collected monthlysince 1976 by Statistics Canada, questions on hourly wages and union status havebeen included in the survey questionnaire only since 1997. The surveys mentionedabove are supplements to the LFS and were collected by asking LFS respondentsto answer additional questions. As the survey years indicate, these supplementalsurveys were not conducted on an annual basis.5 The LMAS follows individuals

4 The Survey of Consumer Finances provides data on weekly earnings, but does not provideinformation on union status or detailed information on industry of affiliation.

5 With the exception of the 1991 Survey of Work Arrangements, all the supplements that werecollected between the years 1981 and 1998 are used. The 1991 Survey is excluded because thehourly wage data are reported as a categorical variable rather than as a continuous variable.Starting in 1993, Statistics Canada collected data for the Survey of Longitudinal IncomeDynamics (SLID). Although the SLID contains detailed information on the industry ofaffiliation and union status, these data were not used for this study because the hourly wageconcept was not comparable to that of the LFS and its supplemental surveys.

76 J. Townsend

for several years; to control for the panel aspects of these data sets, I allow theregression error of the first stage regression to be correlated across years forindividuals that appear in more than a single year of data.6

For each survey year, I retain those individuals aged 16–647 that are paid work-ers and were members of the labour force during November of the year of thesurvey. I examine the usual hourly wage from the main job held in that month,with the main job defined as the one with the most hours per week. I do notinclude overtime wages in my analysis. All wages are converted to 1998 dollarsusing the CPI. In January 1990 the LFS changed the way in which educational in-formation was collected. Prior to 1990 individuals who did not finish high schoolbut completed a post-secondary diploma were grouped with those individualswith some high school education. After 1990 these individuals are included withthose individuals who completed both high school and a post-secondary diplomaor certificate. As a result of these changes, my educational groups are not per-fectly comparable before and after 1990. To minimize the effect of this change,I use three broad educational groups based on the level of attainment: (i) up toeight years, (ii) from nine years through to some post-secondary, including com-pletion of a post-secondary certificate, and (iii) completion of a university degree.However, the fact of this seam in the data should be kept in mind.

In each survey year, for each job held, the individual is asked to identify theindustry in which he is employed. On the public use tapes, industry information isreported at the 2-digit SIC level.8 For most years, the industry categories availablein mineral mining and manufacturing match up with the 22 industries used inGaston and Trefler (1997) and the 19 manufacturing industries used in Beaulieu(2000). The 1997 and 1998 LFS are exceptions; for these years, the ‘miscellaneousmanufacturing’ category includes tobacco products, leather products and coaland petroleum products. In previous years, these three industry groupings areidentified as distinct categories, in addition to the miscellaneous category. Tocreate a consistent set of industries across the period under study, I roll these fourindustries together in the pre-1997 data sets to form a ‘miscellaneous’ categoryconsistent with the miscellaneous category in LFS. This leaves me with 18 mineralmining and manufacturing industry categories. The Canadian and Americantariff series for the new miscellaneous category is an employment weighted averageof the tariffs for the four industries forming this group.

The tariff and American employment series are from the same sources that wereused in Gaston and Trefler (1997) and Beaulieu (2000). The tariff figures are fromMagun et al. (1988). Figures for American employment are from the Earnings and

6 There are two panels in the LMAS. The first spans the period 1986–7, while the second spansthe period 1988–90.

7 I discard those individuals aged 16–19 claiming to have at least some post-secondary educationand those individuals aged 16–24 claiming to have a university degree.

8 In 1981 industry classifications were according to the 1970 SIC. This was changed to the 1980SIC for the remaining years in the data used here. The 1980 revision was reasonably minor,suggesting that the industry groups for 1981 and the remaining years are comparable.

Do tariff reductions affect wages? 77

02

46

8T

ariff

Rat

e (%

)

1980 1985 1990 1995 2000Year

Canadian Tariff American Tariff

FIGURE 1 Average tariff rates, 1979–98NOTES: The average tariffs are weighted averages. Each industry is weighted by total Canadianemployment in that industry in 1988.

Employment series available from the Bureau of Labour Statistics (BLS) and arereported for all workers. Employment figures for the four industries making upthe miscellaneous category are summed together. Industry specific real exchangerates were calculated using real exchange rate data from the Penn World Tablesand industry-level trade data from the Strategis Web site maintained by IndustryCanada (strategis.ic.gc.ca). The real exchange rate for each industry is a weightedaverage of the real exchange rates of each of the top 10 trading partners for thatindustry, based on the sum of imports and exports over the period 1991–8.9 Theaverages are weighted according to each country’s share of exports and importsover the specified period.

4. Empirical results

4.1. A first look at the data

4.1.1. Wage and tariffs over the period 1981–98I begin with a brief description of the broad wage and tariff developments duringthe study period. Figure 1 shows the employment weighted average Canadian

9 These years were chosen on the basis of data availability.

78 J. Townsend

101114

20

22

23

24

25

2627

28

30

3233

34

35

36

37

65

05

1015

Am

eric

an T

ariff

0 5 10 15 20Canadian Tariff

FIGURE 2 The 1988 tariff structureNOTES: The fitted line was obtained by regressing the American tariff on the Canadian tariff.Numbers denote industries and are based on SIC80 categories: 22 – textiles; 23 – clothing; 25 –furniture and fixtures; 30 – Rubber and plastics. For additional codes, see table 1.

and American bilateral tariffs over the period 1979–98. Average tariffs fell priorto 1988 as both countries honoured their commitments to the Tokyo round ofGATT. The decreases after 1988 are a result of CUSFTA. The ‘kink’ at 1993 isrelated to the staging process; some tariffs were phased out over five years, whileothers were phased out over 10 years. Figure 2 shows the Canadian and Americantariffs by industry in 1988. The tariffs are highly correlated, with the two countriesprotecting the same industries. Given this high degree of correlation, it may notbe possible to identity separate effects on wages of reductions in the two tariffs.

As noted in section 1, the Tokyo Round of the GATT reductions had littleeffect on the tariff structure, as high-tariff industries in 1981 remained high-tariffindustries in 1987. In contrast, the CUSFTA cuts eliminated the tariff structure,as all bilateral tariffs were zero in 1998. Table 1 lists the Canadian tariffs againstU.S. imports and the mean log wages for each industry in the data set for theyear 1988, along with changes in the wages and tariffs over the periods 1981–8 and 1988–98. These years were chosen because they represent similar pointson the business cycle. Furthermore, 1988 is the year immediately prior to theimplementation of CUSFTA, while 1998 is the year in which the tariff cuts werecompleted. The last three rows of table 1 provide averages for the six industries

Do tariff reductions affect wages? 79

TABLE 1Average hourly wages and tariffs by industry, 1981, 1988, and 1998

1988 Can. 1988 Mean �τ �W �τ �WCode industry tariff, τ , log wage W 81–8 81–8 88–98 88–98

23 Clothing 17.2 2.32 −0.5 −0.01 −17.2 −0.0725 Furniture & fixtures 12.6 2.53 −4.1 0.01 −12.6 −0.0922 Textiles 9.9 2.51 −0.8 0.05 −9.9 −0.0430 Rubber & Plastics 8.9 2.75 −3.8 0.18 −8.9 −0.1334 Metal fabricating 6.8 2.75 −3.5 0.06 −6.8 −0.0736 Electrical equipment 6.1 2.73 −4.3 0.04 −6.1 0.1128 Chemicals 5.6 2.90 −1.8 0.06 −5.6 −0.0565 Miscellaneous manuf. 5.3 2.67 −2.3 0.11 −5.3 0.0235 Machinery 4.7 2.82 −3.1 0.00 −4.7 −0.0120 Food & beverages 4.2 2.62 0.0 0.06 −4.2 −0.0326 Paper 4.0 2.99 −3.2 0.16 −4.0 −0.0133 Primary metal manuf. 4.0 2.91 −1.6 0.02 −4.0 0.0432 Non-metal manufact. 3.4 2.80 −2.3 0.11 −3.4 −0.0724 Wood 2.7 2.73 −1.8 0.00 −2.7 −0.0937 Transportation equip. 2.3 2.86 −0.5 0.03 −2.3 0.0426 Printing 1.4 2.68 −3.2 0.09 −1.4 −0.0814 Non-metal mining 0.5 2.85 −0.2 −0.02 −0.5 −0.0511 Metal fuels mining 0.4 3.09 −0.3 0.16 −0.4 −0.0510 Metal mining 0.1 3.05 −0.1 0.09 −0.1 0.06

High tariff 10.3 2.60 −2.8 0.06 −10.3 −0.05Medium tariff 4.5 2.82 −2.1 0.07 −4.5 −0.02Low tariff 1.2 2.88 −1.0 0.06 −1.2 −0.03

NOTE: Tariffs are reported as rates. For example, in 1988 tariffs applied to clothing imports averaged17.2% of the value of the imported good.SOURCE: Estimates by the author, using data from the 1981 Survey of Work History, the 1988Labour Market Activities Survey, and the 1998 Labour Force Survey

with the highest tariffs in 1988, along with averages for the six industries with thethe lowest tariffs and the remaining seven industries with ‘medium’ tariffs. As agroup, the industries with the highest tariffs in 1988 also tended to also have thelowest hourly wages. An examination of the wage series suggests that wages grewmodestly over the pre-CUSFTA period. In contrast, wages over the CUSFTAperiod tended to decline. The coefficient of correlation between the change in themean log wage and the change in tariff rate over the Tokyo round period (1981–8)is −0.18; for the CUSFTA period, the coefficient of correlation is 0.30.

4.1.2. Worker characteristics by industryTable 2 presents the mean characteristics of workers in the panel of tradable goodsindustries for the years 1981, 1988, and 1998. Taken as a whole, the ‘tradables’sector is highly unionized and employs mostly men. The gender ratios have beenremarkably constant over the study period. Union membership has declined be-tween 1988 and 1998. This decline in unionization of the Canadian workforce has

80 J. Townsend

TABLE 2Worker demographics, ‘tradables’ sector only

1981 1988 1998

Union membership 44.1 43.1 36.2Male 74.1 73.2 74.2Educational attainment0–8 years 20.7 14.4 6.7Some high school 73.7 78.6 84.4to competition of aPost-secondary certificateUniversity Degree 5.6 7.0 8.9Age (in years)16–24 22.7 15.1 11.725–34 29.6 32.9 25.135–44 21.1 27.5 33.345–54 16.1 16.3 22.755–64 10.4 8.2 8.2Job tenure1–6 months 19.4 15.0 11.57–12 months 8.7 11.0 7.11–5 years 28.2 29.0 27.26–10 years 17.8 16.4 16.011–20 years 15.8 21.6 21.3Over 20 years 10.2 10.8 16.9

NOTE: Figures show the proportion of workers within a group that have a certain trait.SOURCE: Estimates by the author, using data from the 1981 Survey of Work History, the 1988Labour Market Activities Survey, and the 1998 Labour Force Survey

also been documented in Morissette, Schellenberg, and Johnson (2005). The skillscontent of the workforce is measured using educational attainment, accordingto the three categories described in section 3. Educational attainment has beengradually increasing, as the fraction of the workforce with less than eight yearsof schooling has fallen, and the fraction of the workforce with a university de-gree has risen. The workforce has also become older; this pattern reflects the agestructure of the Canadian population as a whole.

At a more disaggregate level, industry distributions of worker characteristicsare presented in tables 3 and 4. In each table, industries are sorted in descend-ing order according to the 1988 tariff rate against American imports. Table 3shows the proportion of workers who have union membership and the propor-tion of workers who were male in each industry for the years 1981, 1988, and1998. The last three rows report the same statistics for the unweighed mean ofthe six industries with the highest and lowest tariffs, along with the mean for theseven industries with ‘medium’ tariffs in 1988. Two trends are suggested by thelast three rows. First, the most protected industries have historically had lowerunionization rates on average than the least protected industries. Furthermore,over the study period, union membership has declined across all industries, with

Do tariff reductions affect wages? 81

TABLE 3Union coverage and gender breakdown by industry, selected years

Unionization rate (%) Male (%)1988 Can.Industry tariff 1981 1988 1998 1981 1988 1998

Clothing 17.2 43 51 28 22 26 25Furniture & Fixtures 12.6 31 27 23 77 75 78Textiles 9.9 46 45 38 46 59 59Rubber & Plastics 8.9 37 40 30 71 79 73Metal fabricating 6.8 44 46 28 87 87 84Electrical equipment 6.1 44 34 26 61 70 68Chemicals 5.6 30 30 18 73 66 59Miscellaneous manuf. 5.3 37 26 19 59 60 61Machinery 4.7 40 31 27 80 82 87Food & Beverages 4.2 41 46 38 64 66 62Paper 4.0 70 73 61 87 89 85Primary metal manuf. 4.0 58 54 54 94 83 89Non-metal manufact. 3.4 44 55 42 82 82 89Wood 2.7 52 48 34 91 89 88Transportation equip. 2.3 67 62 56 88 81 80Printing 1.4 37 26 22 56 51 59Non-metal mining 0.5 67 49 37 93 85 92Metal fuels mining 0.4 36 23 21 74 80 73Metal mining 0.1 67 60 55 92 93 88High tariff 10.25 41 40 29 61 66 65Medium tariff 4.45 46 45 37 77 75 76Low tariff 1.23 54 45 37 82 80 80

SOURCE: Estimates by the author, using data from the 1981 Survey of Work History, the 1988Labour Market Activities Survey, and the 1998 Labour Force Survey

most of the decline occurring in the 1990s. The decline appears more pronouncedin the high-tariff sector. Second, industries that have traditionally received highlevels of protection also employ a higher proportion of women. This result ispartly skewed by the inclusion of the clothing industry, which predominantlyemploys women. Even within narrow industry categories, the gender ratios showlittle change over the study period.

Patterns of employment based on age and educational attainment are exam-ined in table 4. Columns 2–4 show the fraction of the workforce that is between16 and 34 years of age. There is no obvious relationship between the level oftrade protection and the age of the workforce. The average age or the workforcehas been increasing in all industries. The last three rows indicate the fractionof the workforce with a university degree. The chemical industry and the elec-tronic equipment industry stand out as industries with highly educated work-forces. The fraction of the workforce with a university degree has been growingfor middle- and high-tariff industries. These tabulations are consistent with thefinding by Beaulieu (2000) that the CUSFTA cuts were associated with skillsupgrading in those sectors facing the heaviest cuts. Beaulieu used production and

82 J. Townsend

TABLE 4Proportion of unskilled and young workers by industry, selected years

Workforce aged 16–34 University degree (%)1988 Can.Industry tariff 1981 1988 1998 1981 1988 1998

Clothing 17.2 51.4 47.3 23.7 1.2 1.5 3.8Furniture & Fixtures 12.6 52.0 60.0 47.1 3.1 3.6 7.7Textiles 9.9 52.0 45.9 33.7 3.0 3.4 8.0Rubber & Plastics 8.9 57.0 57.0 41.9 3.3 5.6 5.8Metal fabricating 6.8 51.0 53.7 45.4 3.3 2.6 5.8Electrical equipment 6.1 48.1 47.5 34.2 10.5 14.5 18.8Chemicals 5.6 44.7 45.7 32.1 16.3 14.5 28.3Miscellaneous manuf. 5.3 59.8 49.3 39.1 8.3 10.5 11.9Machinery 4.7 46.3 54.6 40.7 7.3 7.7 9.9Food & Beverages 4.2 55.5 51.3 40.3 3.2 4.4 7.2Paper 4.0 43.0 34.9 25.4 2.9 5.5 8.1Primary metal manuf. 4.0 52.6 43.9 24.6 5.1 9.1 9.6Non-metal manufact. 3.4 46.1 47.3 27.3 5.7 5.3 5.8Wood 2.7 58.4 54.4 42.8 2.7 3.4 4.0Transportation equip. 2.3 47.5 46.1 33.3 5.7 4.9 7.5Printing 1.4 59.6 55.3 43.5 8.4 9.6 10.2Non-metal mining 0.5 51.5 46.8 28.6 4.1 7.2 2.9Metal fuels mining 0.4 53.9 44.4 33.5 13.5 18.6 14.0Metal mining 0.1 54.9 35.0 21.9 7.9 5.4 7.3High tariff 10.25 51.9 51.9 37.7 4.1 5.2 8.3Medium tariff 4.45 49.7 46.7 32.8 7.0 8.1 11.5Low tariff 1.23 54.3 47.0 33.9 7.1 8.2 7.7

SOURCE: Estimates by the author, using data from the 1981 Survey of Work History, the 1988Labour Market Activities Survey, and the 1998 Labour Force Survey

non-production workers as proxies for less and more skilled workers. Here,levels of educational attainment show a similar relationship with the tariffcuts.

The employment patterns described above have conflicting implications forunconditional wage movements within and across manufacturing industries. Skillupgrading and an aging, more experienced workforce should have resulted inhigher wages in all industries. Educational attainment increased in sectors withmedium and high tariffs, suggesting that in the absence of other changes (e.g.,CUSFTA) the wage gap between high- and low-tariff industries should havedeclined. In contrast, declining coverage rates across industries may have workedto reduce mean wages. In his survey on union wage effects, Kuhn (1998) reportsthat there is substantial empirical evidence that otherwise identical workers inNorth America earn 15% more when the job is unionized. Given that unionrates dropped off somewhat more rapidly in the high-tariff sector over the period1988–98, the wages in these sectors should have fallen relative to those in thelow-tariff sector. These patterns suggest that the aggregate earnings measuresused in previous studies of CUSFTA may have been influenced by a variety

Do tariff reductions affect wages? 83

of compositional effects, and that the results of Gaston and Trefler (1997) andBeaulieu (2000) cannot be interpreted as showing that there was no change in theconditional hourly wage rate.

4.2. Regression resultsIndustry premia are estimated using three specifications. In the first specification,worker characteristics are ignored and average wages by industry are estimateddirectly from the data. Since these averages are not conditional on worker char-acteristics, the subsequent tariff effect can be compared with those found in theprevious studies of CUSFTA, which relied on industry averages. In the secondspecification, equation (1) is estimated with the restriction that the coefficients onindividual characteristics are constant across all years. This specification controlsfor changes in the composition of the workforce, but not for changes in the pricesof characteristics over time. In the third specification, the industry effects are es-timated using the general model implied by equation (1), in which the coefficientson worker characteristics are allowed to vary across years. In each specification,the industry premia and, where applicable, the ‘prices’ of characteristics, are es-timated separately for the union and non-union sectors.

Table 5 presents the results obtained by estimating equation (1) using thesecond specification, where the coefficients on worker characteristics are commonacross all years.10 The results are consistent with previous estimates of wageequations. Based on observable characteristics, women have lower earnings thanmen in both the union and the non-union sectors. Higher educational attainmentand longer job tenure are associated with higher earnings. In the union sector,there is a tendency for the wage structure to be more compressed; the returns to jobtenure, age, and education are substantially smaller than in the non-union sector.The tendency for unionization to result in compression of the wage structure hasbeen found in other studies of the effects of unions on wages. These findings aresummarized in Kuhn (1998).

Table 6 shows the estimated wage premia for 1988 obtained from the model inwhich coefficients on worker characteristics are held constant across years. Thelast two columns also show the number of observations for each industry that theestimates are based on. As noted previously, an industry premium is a measure ofhow the wages in an industry deviate from the industrial mean for workers that areidentical on the basis of their observable characteristics. A comparison of tables1 and 6 indicates that controlling for individual characteristics does not changethe general pattern. The industries with the highest tariffs in 1988 tended to havethe lowest earnings, after worker characteristics are controlled for. This patternholds for workers in both the non-union and union sectors. Computing industrypremia while allowing the returns to characteristics to vary across years does notgreatly affect the qualitative nature of the premia. For example, the correlations

10 The third specification involves estimating this wage equation for each year of data. Owing tospace constraints, these results are not reported here.

84 J. Townsend

TABLE 5The estimated wage equation when returns to characteristics are constant across all years

Non-union Union Non-union Union

Male 0.269 0.214 Province(0.004) (0.005) Quebec 0.112 0.11

Educational attainment (0.007) (0.006)8 or fewer years −0.188 −0.088 Ontario 0.183 0.167

(0.007) (0.005) (0.006) (0.005)University degree 0.287 0.102 Manitoba and 0.079 0.128

(0.006) (0.011) Saskatchewan (0.008) (0.007)Age Alberta 0.202 0.24925–34 0.225 0.137 (0.008) (0.009)

(0.006) (0.006) British Columbia 0.25 0.3135–44 0.288 0.169 (0.009) (0.007)

(0.006) (0.007) Constant 1.98 2.2445–54 0.288 0.174 (0.01) (0.01)

(0.007) (0.007) R2 0.45 0.4455–64 0.242 0.139 Sample size 38139 27096

(0.009) (0.008)Job tenure7–12 months 0.051 0.016

(0.008) (0.008)1–5 years 0.127 0.05

(0.006) (0.007)6–10 years 0.236 0.081

(0.007) (0.007)11–20 years 0.303 0.104

(0.007) (0.007)Over 20 years 0.37 0.147

(0.009) (0.008)

NOTE: Standard errors of estimates in parentheses. The dependent variable is the log of the hourlywage. The results are obtained using constrained least squares, with the industry premia (see table 6)constrained to sum to one.

between the 1988 industry premia shown in table 6 and the equivalent estimateswhen the more general model is estimated is 0.99. Gera and Grenier (1994) use the1986 LMAS to estimate industry premia for Canada. The results shown in table6 are similar to those presented in table 2 of Gera and Grenier (1994). The resultsare not strictly comparable; Gera and Grenier include all industries, rather thanjust the tradable goods sector, and use an expanded set of explanatory variablesin the wage regression. These additional variables were not used here, as they arenot available in all of the surveys I use.

Equation (2) was estimated using the estimates of the industry premia ob-tained from each of the three specifications of the first stage regression describedabove. Results are presented in table 7. The model was first estimated by pool-ing together the union and nonunion premia and estimating a restricted modelin which the coefficients are held constant across the two sectors. In addition,the model was estimated separately according to union status. In each case, the

Do tariff reductions affect wages? 85

TABLE 6The estimated 1988 industrial premia corresponding to table 5

1988 Can. Industry premia No. of observationsa

Industry Tariff Non-union Union Non-union Union

Clothing 17.2 −0.24 −0.35 128 75(0.03) (0.03)

Furniture & fixtures 12.6 −0.18 −0.24 103 37(0.04) (0.04)

Textiles 9.9 −0.20 −0.11 86 62(0.04) (0.03)

Rubber & Plastics 8.9 0.04 −0.06 175 74(0.03) (0.03)

Metal fabricating 6.8 −0.06 0.00 201 110(0.03) (0.03)

Electrical equipment 6.1 0.00 −0.06 185 91(0.03) (0.03)

Chemicals 5.6 0.10 0.14 161 60(0.03) (0.03)

Miscellaneous manuf. 5.3 −0.02 −0.06 240 64(0.02) (0.03)

Machinery 4.7 0.05 −0.03 139 68(0.03) (0.03)

Food & beverages 4.2 −0.11 −0.11 622 490(0.02) (0.01)

Paper 4.0 0.15 0.19 155 427(0.03) (0.01)

Primary metal manuf. 4.0 0.07 0.11 158 204(0.03) (0.02)

Non-metal manufacturing 3.4 −0.01 −0.03 88 81(0.04) (0.03)

Wood 2.7 −0.05 −0.03 275 221(0.02) (0.02)

Transportation equipment 2.3 0.04 0.08 223 309(0.02) (0.02)

Printing 1.4 −0.11 0.06 320 67(0.02) (0.03)

Non-metal mining 0.5 0.06 0.11 53 58(0.05) (0.03)

Metal fuels mining 0.4 0.23 0.18 295 119(0.02) (0.02)

Metal mining 0.1 0.25 0.19 117 200(0.03) (0.02)

aThe number of observations per industry in 1988NOTES: Standard errors of estimates are in parentheses. Industry premia indicate the deviation ofthe wages of an industry from the cross-industry average for a worker with a given set of observablecharacteristics.

model was estimated using weighted least squares, with the inverse of the stan-dard errors of the industry premia used as weights. The standard errors of thesecond-stage estimates are computed using the Huber/White/sandwich varianceestimator clustered by industry to account for general forms of heteroscedasticityand autocorrelation.

86 J. Townsend

TABLE 7Etimates of the industry premium equation

Returns to characteristics, first-stage regression

Common forNonea all yearsb Varying by yearc

(1) (2) (3) (4) (5) (6) (7)

I. Pooled - Non-unionized andunionized workers

Canadian tariffd 0.009 0.014 0.019 0.032 0.031 0.042∗∗ 0.043∗∗

(0.031) (0.018) (0.025) (0.016) (0.020) (0.014) (0.014)American tariffd 0.007 0.021 0.018

(0.029) (0.023) (0.016)American −0.049 −0.047 −0.056 −0.051∗ −0.037∗ −0.032

employment (0.030) (0.029) (0.022) (0.022) (0.017) (0.016)Real exchange rated −0.014 −0.015 −0.029 −0.033∗ −0.019∗ −0.022∗ −0.019

(0.019) (0.019) (0.011) (0.012) (0.009) (0.009) (0.009)N 380 380 380 380 380 380 380

II. Non-unionizedworkers

Canadian tariffd −0.032 −0.007 0.006 0.029 0.030 0.050∗∗ 0.050∗∗

(0.028) (0.015) (0.028) (0.015) (0.022) (0.014) (0.014)American tariffd 0.038 0.029 0.031

(0.032) (0.029) (0.022)American −0.002 0.010 −0.030 −0.020 −0.004 0.006

employment (0.030) (0.029) (0.034) (0.032) (0.023) (0.023)Real exchange rated 0.025 0.018 −0.002 −0.008 0.008 0.003 0.002

(0.025) (0.022) (0.012) (0.013) (0.008) (0.008) (0.009)N 190 190 190 190 190 190 190

III. Unionizedworkers

Canadian tariffd 0.048 0.040 0.036 0.045∗ 0.039 0.042∗∗ 0.044∗∗

(0.036) (0.022) (0.030) (0.021) (0.027) (0.016) (0.015)American tariffd −0.013 0.014 0.004

(0.046) (0.044) (0.035)American −0.082∗ −0.086∗ −0.063∗ −0.06∗ −0.059∗∗ −0.058∗∗

employment (0.038) (0.039) (0.026) (0.027) (0.019) (0.020)Real exchange rated −0.045∗ −0.043 −0.053∗∗ −0.056∗∗ −0.051∗∗ −0.052∗∗ −0.048∗∗

(0.019) (0.021) (0.014) (0.017) (0.013) (0.016) (0.016)N 190 190 190 190 190 190 190

aIndustry premia are based on mean log wages by industry, conditional only on union membership.bThe regressors in the first-stage regression consist of categorical variables for individuals’ gender,educational attainment, age, job tenure, and region of habitation. See table 5 for coefficient estimates.cThe regressors in the first stage are the same as above. However, the coefficients on thesecharacteristics are allowed to vary from year to year.d For reporting purposes, the estimated values and the standard errors have been multiplied by ten.NOTES: ∗Indicates significance at .10 level, ∗∗Indicates significance at .05 level, ∗∗∗Indicatessignificance at .01 level.Estimated using WLS, with the inverse of the standard error of the wage premia as weights. Correctedfor heteroscedasticity/autocorrelation using White/Huber/Sandwich estimator. Industry and yeareffects are included (not reported).

Do tariff reductions affect wages? 87

When estimating the model with the union and non-union premia pooled to-gether (part I of table 7), both the industry fixed-effects and year dummies wereinteracted with union status. Columns 1 and 2 correspond to the case where noindividual controls are included in the first-stage regressions. Given the corre-lation between the American and Canadian tariffs, the model is estimated withboth tariffs (column 1) and with only the Canadian tariff (column 2). In bothcases, the effect of tariffs on wage premia is negligible and statistically insignifi-cant. Dropping the American tariff reduces the standard error of the estimatedCanadian tariff coefficient, as is to be expected, given the high degree of correla-tion between the two variables. These results parallel the findings of Gaston andTrefler (1997) and Beaulieu (2000) both of which found no relationship betweenthe tariffs and the average earnings of workers, either as a whole or for productionand non-production workers. Including individual controls with time invariantcoefficients in the first stage regression (columns 3–4) increases the magnitudeof the tariff coefficients; however, the results continue to be statistically insignif-icant. Allowing the coefficients on worker characteristics to change from year toyear in the first-stage regression (columns 5–7) further increases the magnitudeof the estimate. When the American tariff is dropped, the effect is statisticallysignificant. The results imply that a 1 percentage point reduction in the tariffresulted in a 0.4% decline in the earnings of workers in the affected industry.The average tariff in 1988 was 5.3%. Based on the estimated tariff coefficient, theCUSFTA cuts are associated with a 2.1% decline in the wages of a worker in anindustry covered by the average tariff relative to a worker in an industry receivingno protection in 1988. Over a 10-year period, this is a small decline in earnings.For the industry with the largest tariff (clothing), the implied decline over thesame period was 6.8% This is a sizable effect. Recall from the industry premiapresented in table 6 that the wages in this industry were already low in relativeterms. The adverse effects of the agreement were most severe for those least ableto absorb them.

For each specification, the hypothesis that all the coefficients take the samevalue for workers in the union and non-union sectors can be rejected at the 0.01level of significance for each of the seven specifications. In contrast, the hypothesisthat the coefficients on the tariff terms are the same cannot be rejected at the0.10 level of significance. Parts II and III of table 7 report the results when thesecond-stage model is estimated separately for non-union and union workers.For the specifications where the first-stage regression does not include individualcontrols (columns 1–2) or does not allow the returns to characteristics to vary byyear (columns 3–4), the coefficient on the Canadian tariff is larger in magnitudein the union sector than in the non-union sector. In each case, the estimatedeffect is statistically insignificant. In the specifications allowing for time-varyingcoefficients on worker characteristics (columns 5–7), tariffs show a positive andsignificant effect on the wages in both sectors once the American tariff is dropped.The magnitude is approximately the same in both sectors and is comparable to thevalue estimated when the two sectors were pooled. The most striking differences

88 J. Townsend

between the union and non-union sectors are the ways in which the wages for thetwo types of workers respond to changes in American employment and changesin the real exchange rate. Wages in the non-union sector are not responsive tochanges in these variables. In contrast, appreciation in the real exchange rate wasassociated with falling wages in the union sector, while wages increased in thoseindustries for which employment was falling in the counterpart industry in theUnited States.

American employment is expressed as the logarithm of total employment inthe industry. Using the point estimate in column 6 for unionized workers, a 0.1log point decline (roughly 10%) in employment in the counterpart U.S. industry isassociated with a 0.006 log point increase (roughly 0.6%) in earnings. To put thisnumber in context, the largest American employment losses over the period 1988–98 occurred in the clothing sector, where the change was −0.35 log points. Thepoint estimate on the American employment coefficient indicates that these losseswere associated with a 0.021 log point gain in the wages of unionized Canadianworkers in the clothing sector. Recall that the American employment variable wasincluded to control for changes in demand for labour at the industry-level arisingfrom changes in technology and trade with countries outside the free trade area.Sectors with large declines in employment after 1988 included clothing (−0.35 logpoints) and textiles (−0.20). These findings are not surprising, given that thesegoods are amenable to being-produced in developing countries with low wages.If the American employment variable effectively controls for such changes, apuzzle arises: why were wages in the union sector able to rise as external pressuresdecreased the demand for workers? If these industries are truly in permanentdecline, with more and more production of these goods happening abroad, thenperhaps workers are engaged in the kind of ‘end game’ outlined by Lawrence andLawrence (1985). Lawrence and Lawrence argue that the ability of a union tocapture rents decreases with the elasticity of the demand for labour. Elasticity willbe high in an expanding industry, where the scope for new investment will allowfor the substitution of capital for labour. In contrast, in a contracting industrythere will be little new investment, which will tend to limit the substitutability ofcapital for labour and may enable the union to capture a greater share of rents.

The real exchange rate is an index that is normalized to 100 for all industries in1988. Again using the point estimate, a 1-point appreciation in the real exchangerate is associated with a 0.005 log point decline in relative wages. Although thereis considerable variation across industries, real exchange rates tend to be risingprior to 1991. After 1991 exchange rates fall in all industries. Given the relativeimportance of the United States in the trade flows of all Canadian industries,the industry-specific real exchanges tend to move together. However, there aredifferences as well; in 1998 the real exchange rate index for the Canadian clothingsector was 92, compared with an average rate across industries of 83. The pointestimate of the exchange rate coefficient indicates that wages in the clothingsector were 0.045 log points lower than the industry average as a result of highreal exchange rates specific to the industry. Arguably, higher exchange rates would

Do tariff reductions affect wages? 89

TABLE 8Regression diagnostics for column 6 of table 7

(1) (2) (3) (4)

I. Non-unionizedworkers

Canadian tariffa 0.043∗∗ 0.041∗∗ 0.043 0.049∗∗∗

(0.020) (0.027) (0.030) (0.014)American employment 0.034 −0.006 0.001 0.006

(0.052) (0.025) (0.025) (0.023)Real exchange ratea 0.004 0.009 0.001 0.002

(0.009) (0.015) (0.002) (0.009)N 160 180 170 190

II. Unionized workersCanadian tariffa 0.033∗ 0.034∗∗ 0.033 0.047∗∗

(0.020) (0.022) (0.026) (0.017)American employment −0.055 −0.072 −0.071 −0.058∗∗

(0.041) (0.027) (0.028) (0.021)Real exchange ratea −0.056∗∗∗ −0.028 −0.028 −0.051∗∗∗

(0.018) (0.014) (0.016) (0.016)N 160 180 170 190Specification Excludes mining Excludes clothing Excludes clothing IV, 1988 tariffsnotes industries and Furniture phased out

over 10 years

aFor reporting purposes, the estimated values and the standard errors have been multiplied by ten.NOTES: ∗Indicates significance at .10 level, ∗∗Indicates significance at .05 level, ∗∗∗Indicatessignificance at .01 level.The returns to characteristics are allowed to vary by year and consist of categorical variables forindividuals’ sex, educational attainment, age, job tenure, and region of habitation. See table 5 forcoefficient estimates. Estimated using WLS, with the inverse of the standard error of the wagepremia as weights. Corrected for heteroscedasticity/autocorrelation using White/Huber/Sandwichestimator. Industry and year effects are included (not reported).

provide some protection against imports; the negative coefficient on this variablesuggests that the real exchange rate affects wages primarily through its effect onthe competitiveness of Canadian exports.

4.3. Robustness of the resultsTo examine the robustness of the results, I re-estimate the model while excludingcertain industries. The results are reported in table 8. In each case, the returnsto individual characteristics are allowed to vary across years, and the controlsin the second stage consist of the Canadian tariff, American employment, andthe real exchange rate; the results are comparable to those in column 6 of table7. In column 1, the three mining industries are dropped from the sample. Theseindustries provide little variation in the Canadian tariff rate over the study period;their inclusion serves mainly to help to identify the coefficients on the othercontrols. Unlike industries in which goods are manufactured, resource rents mayhave been an important determinant of wages in these industries, which suggests

90 J. Townsend

that the wage processes may be quite different in the resource sector. Exclusion ofthese industries does not substantially alter the results in either the union or thenon-union sector. The magnitude of the American employment term increasesfor the non-union sector, but is not statistically significant, while the coefficienton this term is no longer significantly different from zero in the union sectoronce these industries are excluded. I also examine the effects of removing theindustries with the greatest variation. In column 2 the results are reported whenthe clothing industry is excluded. In column 3 results are reported when theclothing and the furniture and fixtures industries are removed. The main effectof these exclusions is to reduce the statistical significance of the tariff coefficient.This is not surprising, as these industries are sources of substantial variation inthe tariff series. After these two industries are excluded, no remaining industryhad tariffs in excess of 10% in 1988.

As noted earlier, one concern is that the CUSFTA staging periods may havebeen related to the anticipated wage growth in each industry. In particular, slow-growth industries may have received longer phase-out periods. To account forthe possibility of such endogeneity, I constructed a counterfactual set of tariffsfor each industry by taking the 1988 tariff rates and applying a common 10-yearphase-out period to all industries. I also used a five-year phase-out period. Ineach case, the constructed series was highly correlated with the actual tariff rates,resulting in little different in the subsequent regression results. Results obtainedfrom constructing instruments using the common 10-year phase-out are reportedin column 4 of table 8.

The results indicate that CUSFTA had an adverse affect on workers’ wages,regardless of their union membership status. Given the persistence and stabilityof estimates of wage premia in the United States, Katz and Summers (1989)argue that the wage premia are evidence of rent-sharing between employees andfirms. Changes in the wage premia may reflect either (i) changes in availablerents to be shared between firms and employees, or (ii) short-term differentialscreated in response to changes in labour market conditions if workers are notperfectly mobile across industries. It seems somewhat unlikely that the effectof CUSFTA on wages was the result of eroding rents in the most protectedsectors. High-tariff industries had lower wages than average in 1988, suggestingthat workers in these industries were receiving little in the way of rents to beginwith. If CUSFTA resulted in a restructuring of Canadian manufacturing, andthe observed effect on wages are a result of labour markets adjusting to newpatterns of relative labour demand, then we might expect the changes in the wagedifferentials brought about by CUSFTA to dissipate once the adjustment processis completed. Unfortunately, Statistics Canada changed industrial classificationschemes in 1998, which makes it difficult to carry the analysis forward past theyear in which the tariff cuts were completed.11

11 The Standard Industrial Classification (SIC) has been replaced with the North AmericanIndustry Classification System. The industry categories in the supplements to the LFS have not

Do tariff reductions affect wages? 91

5. Summary and conclusions

The estimates that I obtain using micro data indicate that the changes to the tariffstructure arising from CUSFTA had a substantial effect on the interindustrywage structure in the tradable goods sector in Canada. For non-union workersin affected industries, a 1% reduction in the statutory tariff rate resulted in a0.5% reduction in the wage relative to an observationally equivalent worker inan industry facing no tariff cut. Several industries had tariffs in excess of 10% in1988. Consider an industry with a 1988 tariff rate of 10% and an industry with a1988 tariff close to zero.12 As a result of the CUSFTA cuts, over the period 1988–98 a worker in the previously protected industry experienced a 5% wage declinerelative to her counterpart in the unprotected industry. Results for the unionsector were similar, with workers facing a 0.4% relative wage loss per percentagepoint reduction in the relative tariff. Industries that received high tariff protectionprior to CUSFTA were low-wage industries; as a result of this trade policy, wageinequality across industries increased in the Canadian tradable goods sector.

Gaston and Trefler (1997) and Beaulieu (2000) present evidence that CUSFTAresulted in employment losses in those industries facing the largest cuts. Thesefindings suggest that labour demand was reduced in these industries. Unlikethese previous studies, my analysis indicates that these shifts in demand resultedin declining relative wages. These findings are consistent with a model in whichhuman capital is industry specific. Since skills cannot be transferred betweenindustries, workers may be better off remaining in a declining industry at a lowerwage than they would be by moving to an industry for which they have no skills.As a result, shifts in demand result in persistent changes to the wage.

The results presented here suggest that tariff reductions can have a large effecton the wages of those workers employed in the industries receiving protection. Inthe clothing and furniture industries, tariffs were 17.2% and 12.6%, respectively.These numbers, combined with the point estimate of the tariff effect for non-union workers, imply that relative to mining industries, which had tariffs close tozero in 1988, wages declined by around 8.6% in clothing and 6.3% in furniture.How important are these kinds of effects in the context of the total CUSFTApackage? Based on employment shares, the median tariff in 1988 was 4%. Thisfigure, combined with the point estimate of the tariff coefficient, indicates that themedian worker experienced a relative wage decline of around 2.0% as a result ofCUSFTA. Only 10% of workers were employed in industries with tariffs in excessof 8.9%. For these workers, relative wage losses attributable to CUSFTA wouldbe on the order of 4.5%. The CUSFTA reductions thus had a large effect on therelative wages of workers in those industries facing the deepest cuts. However, asthe tariffs were low for the majority of industries and workers, the overall effectof CUSFTA on the wage distribution in the tradable goods sector was small.

been replaced with the NAICS.12 In 1988 the tariff rate applied to the textiles industry was 9.9%, while the tariffs applied to the

various mining industries were nearly zero.

92 J. Townsend

The discussion in the previous paragraph indicates that while there were biglosers from CUSFTA, the overall effect on the wage structure was modest. Gastonand Trefler (1997) and Beaulieu (2000) reach similar conclusions about CUSFTA,but for a very different reason. They find no direct effect on wages. In contrast, Ishow that once compositional changes in the labour force and changing returns toworker attributes are controlled for, there was a substantial direct effect. However,high-tariff industries accounted for only a small portion of overall employmentin the tradable goods sector, and as a result the overall impact of CUSFTA wassmall. These results still suggest that even when trade occurs between countrieswith similar labour market institutions and factor endowments, liberalizationcan detrimentally affect the relative wages of workers in protected industries. ForCanada, proposals for future trade pacts include those with countries with abun-dant unskilled labour and substantially different labour laws and institutions.Whether liberalization will have a greater impact on the wage structure underthese conditions remains an issue for future research.

References

Beaulieu, Eugene (2000) ‘The Canada-U.S. free trade agreement and labour market ad-justments in Canada,’ Canadian Journal of Economics 33, 540–63

Gaston, Noel, and Daniel Trefler (1995) ‘Union wage sensitivity to trade and protection:theory and evidence,’ Journal of International Economics 35, 1–25

— (1997) ‘The labour market consequences of the Canada-U.S. Free Trade Agreement,’Canadian Journal of Economics 30, 18–41

Gera, S., and G. Grenier (1994) ‘Interindustry wage differentials and efficiency wages:some Canadian evidence,’ Canadian Journal of Economics 27, 81–100

Goldberg, Pinelopi Koujianou, and Nina Pavcnik (2005) ‘Trade, wages, and the politicaleconomy of trade protection: evidence from the Colombian trade reforms,’ Journal ofInternational Economics 66, 74–105

Heston, Alan, Robert Summers, and Bettina Aten (2002) Penn World Table Version 6.1,Center for International Comparisons at the University of Pennsylvania

Katz, Lawrence, and Lawrence Summers (1989) ‘Industry rents: evidence and implica-tions,’ Brookings Papers on Economic Activity, Special Issue 0, 209–75

Kuhn, Peter (1998) ‘Unions and the economy: what we know; what we should know,’Canadian Journal of Economics 31, 1033–56

Lawrence, Colin, and Robert Z. Lawrence (1985) ‘Manufacturing wage dispersion: an endgame intepretation,’ Brookings Papers on Economic Activity 1, 47–106

Magun, S., S. Rao, B. Lodh, L. Lavalee, and J. Pierce (1988) ‘Open borders: an assessmentof the Canada–U.S. Free Trade Agreement,’ Economic Council of Canada DiscussionPaper No. 344

Morissette, Rene, Grant Schellenberg, and Anick Johnson (2005) ‘Diverging trends inunionization,’ Perspectives on Labour and Income 6(4), 5–12

Trefler, Daniel (2004) ‘The long and short of the Canada-U.S. Free Trade Agreement,’American Economic Review 94, 870–895