1

Offshoring and Volatility: Evidence from Mexico’s Maquiladora
Industry
By Paul R. Bergin, Robert C. Feenstra and Gordon H. Hanson

This paper studies the second-moment properties of offshoring, the arrangement
whereby firms carry out particular stages of production abroad. It documents a
new empirical regularity: maquiladora industries in Mexico that are associatedwith U.S. offshoring experience fluctuations in employment that are twice asvolatile as the corresponding industries in the U.S. This finding is not attributable
simply to higher volatility in the overall Mexican economy, nor to the smaller sizeof Mexico’s industries compared to U.S. counterparts. (JEL F1)

Offshoring, the arrangement whereby firms carry out particular stages of production
abroad, has grown over the last fifteen years to become an important part of the traderelationship between the U.S. and Mexico. It is also of growing importance for trade between the
E.U. and emerging economies in Europe, and in global trade with China. In Mexico,
employment in export assembly plants engaged in production for foreign firms grew ten-fold________________________* Bergin: Department of Economics, University of California at Davis, One Shields Ave., Davis,
CA 95616 USA (e-mail: prbergin@ucdavis.edu); Feenstra: Department of Economics, Universityof California at Davis, One Shields Ave., Davis, CA 95616 USA (e-mail:rcfeenstra@ucdavis.edu,); Hanson: University of California, San Diego, 9500 Gilman Dr., MC:0519 La Jolla, CA 92093-0519 USA (e-mail: gohanson@ucsd.edu). We thank Thomas Chaney,
Fabio Ghironi, Gianmarco Ottaviano, Jonathan Vogel, and seminar participants at the NBER
Summer Institute 2007, ASSA 2007 meetings in Chicago, UC San Diego, Carnegie Mellon
University, Princeton University, University of Colorado, University of Paris, University ofSouthern California, and the International Monetary Fund for helpful comments. Financial support
was provided by the National Science Foundation grant SES-031769.

1from 0.12 million in 1980 to 1.2 million in 2006. The sector accounts for just under 3 percent
ofMexico’s total GDP, 20 percent of Mexican manufacturing value added, and nearly half of thecountry’s exports. While Mexican officials have hailed the export assembly plants for theircontribution to economic growth, some have also complained that the sector is fickle and subject
to excessive volatility.1 The assembly plants, known as maquiladoras, are seen as a channel bywhich the U.S. exports to Mexico a portion of its employment fluctuations over the businesscycle. This phenomenon is beginning to be investigated in the literature on real business cycles
across countries. Our paper is unique in focusing on the maquiladora sector and on cross-country
comparisons of volatility.2
We begin by documenting the variance in offshoring industries in Mexico. These
industries are composed of maquiladoras which U.S. and other foreign firms use to assemble
inputs into final outputs. The data cover Mexico’s four largest offshoring industries, which
together account for three quarters of maquiladora production in the country: apparel,transportation equipment, computers and electronics, and electrical machinery. We match theseindustries to their counterparts in the United States. The main empirical result is that in all four
maquiladora industries the volatility of economic activity in Mexico is significantly higher thanin the U.S.; averaging over the four industries, volatility in Mexico is twice as high as in the U.S.

1

See for example the news account of how the Mexican car industry is highly susceptible tofluctuations in demand for American brand automobiles in Marla Dickerson (2005).
2
Ariel Burstein, Johann Kurz, and Linda Tesar (2008) study the implications of multinational
production for international macroeconomic comovement; as such, their focus is on covariancesacross countries, rather than on comparing variances, which is our focus. For other work on
intermediate inputs and business cycle synchronization see Ayhan M. Kose and Kei-Mu Yi(2001, 2006) and Steve Ambler, Emanuela Cardia, and Christian Zimmerman (2002). See also
David Thesmar and Mathias Thoenig (2007) on vertical separation and employment and sales
volatility in French firms.

2
One might suspect that this finding simply reflects higher volatility in the Mexican
economy overall. That conjecture is not true for employment volatility, which is lower in
Mexico. A second conjecture might be that higher volatility in Mexico reflects the smaller size ofindustries in Mexico. However, our results are robust to comparing Mexican industries with themore similarly sized industries of U.S. border states.3
Finally we decompose this effect into its extensive and intensive margins, where theextensive margin is measured using data on the number of plants operating each month in themaquiladora sector, and the intensive margin is measured using data on average employment perplant. Volatility is present along both of these margins.
Section I of the paper describes relevant background of the maquiladora sector, section II
presents the main results characterizing employment volatility, section III decomposes the effectinto intensive and extensive margins, and section IV concludes.

I. The Maquiladora Sector

3

A third conjecture might be that labor-market institutions differ between the countries, suchthat it is easier to hire and fire employees in Mexico. However, when Juan C. Botero et al. (2004)
rank countries in terms of job security laws restricting the hiring and firing of workers, Mexico
ties for the most regulated among the 85 countries in the sample, whereas the U.S. ranks as thefifth least regulated economy in this respect; these data are used in the analysis of volatility andcomparative advantage by Alejandro Cunat and Marc J. Melitz (2007). We also see this contrast
in labor market flexibility reflected in our employment data discussed below, in which volatilityof employment in overall Mexican manufacturing is lower than that for U.S. overall
manufacturing. In Mexico, labor unions are active in maquiladoras and other manufacturing
establishments, both of which are subject to Mexican labor law (Rafael Otero and Jose A. Pagan,2002). In practice, collective bargaining agreements in maquiladoras are seen as less restrictive
than in the rest of Mexican manufacturing, in that job classifications tend to be wider and firms
tend to have greater leeway in establishing pay-for-performance schemes (David Fairris, 2003).
At the same time, the decline in unionization in Mexican manufacturing, which has been ongoingsince the 1980s, is less evident among maquiladoras. The net effect of more flexible collective
bargaining agreements but more stable union presence appears to be that differences in labor
relations between maquiladoras and other Mexican manufacturing firms are relatively small.

3
Offshoring by the U.S. to Mexico generally takes the form of U.S. firms producing partsand components, exporting these intermediate inputs to Mexico to be assembled or processed
into final goods, and re-importing the finished products. U.S. firms tend to specialize in R&D,
component production, marketing, and other headquarters activities, while Mexican plants – themaquiladoras – tend to specialize in assembly services.4 Mexico is among the most important
locations for offshoring by U.S. firms and the U.S. is by far and away Mexico’s largest trading
partner. Over the period 2000-2003, the United States was the source country for 73.4 percent of
the inputs imported by maquiladoras in Mexico and maquiladora exports back to the UnitedStates were equal to 5.3 percent of U.S. industry shipments (U.S. International Trade
Commission, 2005).5 Maquiladoras have become an integral part of the Mexican economy, with
their share of national manufacturing employment rising from 4.1 percent in 1980 to 24.5 percent
in 2004 (Gordon Hanson, 2007).

4

The Mexican government measures imports and exports by registered export-assembly plants
in Mexico. Under Mexican trade policy, firms that export their output do not have to pay duties
on any imported intermediate inputs used in production. To obtain duty-free status, a firm mustregister with the government. While under the North American Free Trade Agreement imports
from the United States are not subject to duties in Mexico, imports from most other countries are.
As a result, the vast majority of export-assembly plants in Mexico are registered. (Strictly
speaking, export-assembly plants in Mexico may be registered either as maquiladoras or as
PITEX (Program for Temporary Imports of Articles to be Exported) companies (seehttp://www.economia.gob.mx/). Only the former appear in our data. In 2003, maquiladora
exports to the United States were 2.2 times those by PITEX companies.)
5
These figures apply to the four core offshoring industries, described in the text. Comparing
U.S. imports from Mexico to U.S. industry output may give a deceptive sense of the size of
Mexico’s maquiladora sector relative to U.S. manufacturing. U.S. imports from Mexico include
a substantial component of U.S. value added, in the form of the intermediate inputs produced in
the United States and sent to Mexico for further processing. As an alternative measure of relative
size, one might examine value added in the two countries. Over the period 2000-2003, the ratioof value added in Mexico’s maquiladoras to value added in U.S. manufacturing was 0.034 in thefour core offshoring industries, based on annual data (U.S. International Trade Commission,2005).

4
Mexico first began to allow export assembly plants to operate in the country in the 1960s.
The maquiladora sector did not reach an appreciable size until the government relaxed
restrictions on inbound foreign investment in the 1980s. Initially, U.S. firms offshoring to
Mexico received favorable tariff treatment under the HS9802 provision of the U.S. tariff code
(Robert Feenstra, Gordon Hanson, and Deborah Swenson, 2000). Under HS9802, U.S. firms that
manufacture components at home and have them processed into final goods abroad pay duties on
the foreign value-added only when the goods are brought back into the United States. The North
American Free Trade Agreement (NAFTA) ended special tariff treatment for U.S. firms
offshoring to Mexico. But it did not slow growth in production sharing. Growth in real value
added by maquiladoras accelerated after NAFTA was implemented, roughly tripling between
1994 and 2005. Far from removing the incentive for Mexico to specialize in assembly services,
NAFTA freed resources Mexico had devoted to domestic production to move into export
assembly.
Most offshore production by U.S. firms in Mexico occurs in one of four industries: apparel,
electronic accessories (including computer parts and electronic circuitry), electrical machinery(including televisions and other small domestic appliances), and transport equipment and parts(primarily motor vehicles). Over 1990 to 2005 these four industries accounted for three-quartersof employment in the maquiladora sector. These industries are amenable to global production
sharing because firms need not perform all stages—R&D, component production, final
assembly—in the same location, and the stages vary in their factor intensities, giving
multinational firms an incentive to locate labor-intensive activities in low-wage countries.

II. Volatility in Employment

5
As a measure of volatility, we shall focus on the relative variance of employment in U.S.
manufacturing industries and the plants to which they offshore production in Mexico.6 Thisvariance is computed using the monthly employment of production workers, which is available
for both countries. We match Mexico’s four primary maquiladora industries (assembly ofapparel items; electronic materials and accessories, including computer parts; assembly ofelectrical machinery and equipment; and construction and assembly of transport equipment andparts) with their closest U.S. three-digit industry matches (apparel manufacturing, NAICS 315;computer and electronic product manufacturing, NAICS 334; electrical equipment, appliance,and component manufacturing, NAICS 335; and transportation equipment manufacturing,
NAICS 336). Data are available beginning in 1993.7 However, in late 1994 there was a large
depreciation of the peso, as capital fled Mexico, and in 1995 aggregate output dropped sharply.
Given the exposure of the maquiladora sector to exchange-rate fluctuations, including the pesocrisis years in our sample could make volatility in Mexico’s maquiladora industries seem
artificially high. To avoid this problem, the analysis is limited to the period 1996-2005.

Figure 1 about here.

To provide a visual sense of the relative variation in industry activity in the two countries,
Figure 1 plots the production-worker employment for the four core maquiladora industries overthe sample period. To remove seasonal fluctuations and time trends, each series is seasonally6

In results available on request, we have confirmed that similar findings obtain when using thewage bill for production workers instead of employment.
7
Data for Mexico’s maquiladora industries go back to 1990. However, data on Mexico’s overall
manufacturing sector is only available from 1993 forward, owing to a change in the constructionof the series in that year.

6
adjusted and HP filtered (with smoothing parameter 14400). In each industry, employment in
Mexico is substantially more volatile than in the United States. Table 1, which shows the ratio of
the standard deviations for the production worker employment in Mexican and U.S. industries,
reinforces this perception. In each industry, the standard deviation of Mexican employment isgreater than in the United States, with the Mexico-U.S. ratio averaging 2.3 over the fourindustries.

Table 1 about here.

One simple reason that employment in Mexican industries could be more volatile than their
U.S. counterparts is because at an aggregate level the Mexican economy is also more volatile
than the U.S. economy. That reasoning does not apply for employment, however, since as shownin Table 1, employment of production workers in all manufacturing in Mexico has a lower
monthly standard deviation than in the United States. 8 This may reflect the finding in Botero etal. (2004) that Mexico has more restrictive laws regarding employment security (see note 3).

Table 2 about here.

A second reason for volatility to be higher in the Mexican maquiladora industries is thatthey are smaller than the U.S. industries, so with idiosyncratic shocks across plants, U.S.
employment may be smoothing out shocks. To investigate the size differences between the
8This conjecture does hold for the wage bill, but the extra volatility found in the wage bill for
Mexican maquiladora industries exceeds that found in Mexican manufacturing. The ratio of thewage bill in Mexico to that in the U.S. is 2.0 for offshoring industries and 1.5 for manufacturing
overall.

7
Mexican and U.S. industries, Table 2 reports employment in each industry, showing that in twoof the four industries the U.S. is indeed much larger. We can deal with these size disparities byreducing the geographic coverage of the U.S. series. The vast majority of maquiladoras in
Mexico are located in Mexican border cities and many are linked to production operations on the
U.S. side of the border (Feenstra, Hanson, and Swenson, 2000). This makes U.S. border states anatural geographic unit to which to compare Mexican maquiladora industries.

Table 3 about here.

In Tables 2 and 3, we compare Mexican industries to their counterparts in California andTexas, the two U.S. border states for which industry data are available.9 At the state level, theonly series available for three-digit industries is total employment, including production andnonproduction workers. Table 2 shows that employment in industries in California and Texas issimilar in scale to Mexican industries. Table 3 shows that standard deviations and their ratios
based on state employment data are broadly similar to those obtained for national data: the four
offshoring industries are at least 79 percent more volatile in Mexico than in California, and 64
percent more volatile than in Texas, whereas overall Mexican manufacturing employment is lessvolatile than in either state. We conclude that regardless of the comparison case, themaquiladoras have substantially greater volatility than their corresponding industries in the U.S.,
or than overall manufacturing.

III. Volatility in the Extensive Margin

9

The small number of plants in three-digit manufacturing industries in Arizona and New Mexico
makes industry-level data for these states subject to disclosure restrictions.

8
We next investigate how volatility in maquiladora employment is allocated between theintensive and extensive margins. The greater relative volatility in employment in Mexico’s
maquiladora industries could be due to changes in scale in existing plants or to plants enteringand existing production. We use data on the number of plants operating each month in themaquiladora sector and the average employment per plant. Research on exporting plants in othercountries has found that the sunk costs of becoming an exporter are quite high, with muchsmaller continuation costs of exporting. For example, Sanghamitra Das, Mark J. Roberts andJames R. Tybout (2007) estimate that the sunk costs of becoming an exporter for Colombian
plants are on the order of $1 million, or between 20 percent and 40 percent of the annual export
value (with continuation costs around 1 percent). Those values suggest that movement in and outof exporting status would operate in a lumpy fashion, and only in response to large shocks. Ourdata on the maquiladora plants differs from other country samples in that all of these plants are
involved in export assembly for foreign firms, so plant entry and exit is the same as the exporting
decision.
The monthly standard deviation in the number of plants (logged, deseasonalized and HP
filtered) ranges between 2.1 percent for electrical machinery to 5.2 percent for apparel, with anaverage of 3.1 percent over the four industries. That variation is about two-thirds as much as themonthly standard deviation in employment, and there is a positive correlation between thenumber of plants and employment. We can evaluate the relationship between aggregate
employment and the number of plants more formally along the lines of Jonathan Eaton, SamuelKortum and Francis Kramarz (2004), using the identity:(1)

E
E
N it × it ≡ it × E t ,N it E t9where Eit is employment in industry i at time t, Nit is the number of plants in industry i at t, and Et
is aggregate employment in Mexico at t. From this identity we specify two regression equations:E
ln N it = α 0 + α1 ln it + α 2 E t + ε it
Et

(2)
and

E
E
ln it = β 0 + β1 ln it + β 2 E t − ε it .
N it
Et

(3)

By the logic of least squares, α0 + β0 = 0, α1 + β1 = 1 and α2 + β2 = 1. The relative magnitude of
the coefficients identifies how aggregate shocks affect the number of plants (the extensive
margin) and employment per plant (the intensive margin).

Table 4 about here.

Table 4 reports results for this decomposition exercise. All series have been deseasonalized
and HP filtered and data are pooled across the four offshoring industries. Controls for industry
fixed effects are included in the estimation. In column (1), the estimate for α1 is 0.38 and for α2
is 0.49, where both are statistically significant. In response to an increase the share of aggregate
employment in an offshoring industry (holding aggregate employment constant) over one-thirdof adjustment in industry employment occurs at the extensive margin, and in response to anincrease in aggregate employment (holding the industry employment share constant) nearly onehalf of adjustment in industry employment occurs at the extensive margin.

IV. Conclusion
Global production sharing is responsible for a substantial portion of world trade and is theprimary means through which many developing countries engage in international commerce.
While the expansion of export assembly operations have lead to impressive rates of employment

10
growth in China, Eastern Europe, Mexico, and elsewhere, the implications of global production
sharing for the volatility of economic activity has only recently attracted scholarly attention.
In the case of Mexico, we document that the country’s maquiladora industries experiencefluctuations in economic activity that are twice as volatile as the corresponding industries in the
U.S. These fluctuations are not simply byproducts of higher volatility in the overall Mexican
economy, nor are they the product of the smaller size of the Mexican industries compared totheir U.S. counterparts. We also document that adjustments in the extensive margin account for
one-third to one-half of this employment volatility.
The robust empirical regularity that our paper identifies indicates that offshoring has
implications for recipient economies not previously considered. Further, this finding presents a
new fact useful for guiding and evaluating theoretical research on offshoring.

11
References
Ambler, Steve, Emanuela Cardia and Christian Zimmerman. 2002. “International Transmissionof the Business Cycle in a Multi-Sectoral Model.” European Economic Review, 46(2): 273300.
Botero, Juan C., Simeon Djankov, Rafael La Porta, Florencio López de Silanes, and Andrei
Schleifer. 2004. “The Regulation of labor.” Quarterly Journal of Economics, 119(4): 13391382.
Burstein, Ariel, Johann Kurz, and Linda Tesar. 2008. “Trade, Production Sharing, and theInternational Transmission of Business Cycles.” Journal of Monetary Economics, 55(4):775-795.
Cunat, Alejandro and Marc J. Melitz. 2007. “Volatility, Labour Market Flexibility, and thePattern of Comparative Advantage.” NBER Working Paper 13062.
Das, Sanghamitra, Mark J. Roberts, and James R. Tybout. 2007. “Market Entry Costs, Producer
Heterogeneity, and Export Dynamics.” Econometrica 75(3): 837-873.
Dickerson, Marla. 2005. “Big 3’s woes migrate: Mexico’s dependence on assembling cars for
U.S. automakers puts pressure on its economy as Detroit loses market share to foreigncompetitors.” Los Angeles times Business Section, August 21: 1.
Eaton, Jonathan, Samuel Kortum, and Francis Kramarz. 2004. “Dissecting Trade: Firms,
Industries, and Export Destinations.” American Economic Review, 94(2): 150-154.
Fairris, David. 2003. “Unions and Wage Inequality in Mexico.” Industrial and Labor Relations
Review, 56(3): 481-497.
Feenstra, Robert C., Gordon H. Hanson, and Deborah Swenson. 2000. “Offshore Assembly fromthe United States: Production Characteristics of the 9802 Program.” In The Impact ofInternational Trade on Wages , ed. Robert C. Feenstra, ed., 85-128. Chicago: University of
Chicago Press and the National Bureau of Economic Research.
Hanson, Gordon H. 2007. “Globalization, Labor Income, and Poverty in Mexico.” InGlobalization and Poverty, ed. Ann Harrison, 417-456. , Chicago: University of Chicago
Press and the National Bureau of Economic Research..
Kose, M. Ayhan and Kei-Mu Yi. 2001. “International Trade and Business Cycles: Is Vertical
Specialization the Missing Link?” American Economic Review 91(2): 371-375.
Kose, M. Ayhan and Kei-Mu Yi. 2006. “Can the Standard Real Business Cycle Model Explain the
Relation between Trade and Comovement?” Journal of International Economics 68(2): 267295.
Otero, Rafael, and Jose A. Pagan. 2002. “Unions and Job Queuing in Mexico’s Maquiladoras.”
Eastern Economic Journal, 28(3): 393-407.

12
Thesmar, David and Mathias Thoenig. 2007. “From Flexibility to Insecurity: How Vertical
Separation Amplifies Firm-level Uncertainty.” Journal of the European Economic
Association, 5(6): 1161-1202.
U.S. International Trade Commission. 2005. Industry Trade and Technology Review, USITC
Publication 3762, December/January.

13
Table 1. Relative Volatility in Mexico and U.S. Offshoring Industries:
Production Worker Employment

Electrical
Apparel Machinery
Standard Deviations, Employment (percent)σ (L*i ) (Mex. Industry)σ (Li ) (U.S. Industry)Computer &Electronics

Transport
Equipment

Average

4.52
1.88

4.34
1.68

5.95
2.80

2.96
1.38

4.44
1.94

0.89
1.07

0.89
1.07

0.89
1.07

0.89
1.07

0.89
1.07

2.40

2.58

2.13

2.14

2.31

0.83

0.83

0.83

0.83

0.83

Correlations, Employment
corr (L*i ,Li )

0.49

0.43

0.66

0.45

0.51

corr (L ,L )

0.78

0.78

0.78

0.78

0.78

*

corr (L ,L )

0.56

0.71

0.62

0.68

0.64

corr (Li ,L)

0.66

0.86

0.88

0.63

0.76

σ (L* ) (Mex. Aggregate Manufacturing)σ (L) (U.S. Aggregate Manufacturing)σ (L*i )/σ (Li )σ (L* )/σ (L)**i

Notes:The top potion of the table shows standard deviations (in percent) for the production-worker employment
in specific Mexico and U.S. offshoring industries, and in Mexico and U.S. aggregate manufacturing, andthe ratios of these standard deviations. Each series is in log values, seasonally adjusted, and HP filtered.
Data are monthly from 1996 through 2005. The bottom portion of the table shows correlations between
the various employment series.

14

Table 2. Size of Offshoring Industries in Mexico and the U.S.

NAICS Industry
All maquiladoras (Mexico)
All manufacturing (United States)

Thousands of employees (mean 2000-2005)
MexicoU.S.
Texas
California
1,151.00-----

15,336.70

955.5

1,649.00

315

Apparel

230.8

356.9

--

97.4

334

Computer & Electronics

265.6

1,512.30

132.9

366.6

335

Electrical machinery

100.2

497.5

20.0

38.5

336

Transport equipment

240.7

1,855.80

85.2

137.5

Source: U.S. Bureau of Economic Analysis, Regional Economic Information System,
http://www.bea.gov/bea/regional/reis/; Mexico’s National Institute for Statistics, Geography, andInformatics (INEGI), http://www.bea.gov/bea/regional/reis/.

15
Table 3. Relative Volatility in Mexico and U.S. Offshoring Industries:
Total Employment at the U.S. State Level

Apparelσ (L*i ) (Mex. Industry)σ (L i ) (U.S. Industry)σ (L* ) (Mex. Aggregate Manufacturing)σ (L) (U.S. Aggregate Manufacturing)σ (L*i )/σ (Li )σ (L* )/σ (L)Electrical Computer & Transport
Machinery Electronics Equipment
National Level

Average

4.47
1.58

4.11
1.44

5.50
2.38

2.73
1.05

4.20
1.61

0.77
0.96

0.77
0.96

0.77
0.96

0.77
0.96

0.77
0.96

2.83

2.85

2.31

2.60

2.65

0.80

0.80

0.80

0.80

0.80

California

σ (L*i ) (Mex. Industry)σ (L i ) (Cal. Industry)σ (L* ) (Mex. Aggregate Manufacturing)σ (L) (Cal. Aggregate Manufacturing)σ (L*i )/σ (Li )σ (L* )/σ (L)

4.47
2.25

4.11
2.29

5.50
2.57

2.73
1.3

4.20
2.10

0.77
1.37

0.77
1.37

0.77
1.37

0.77
1.37

0.77
1.37

1.99

1.79

2.14

2.10

2.01

0.56

0.56

0.56

0.56

0.56

Texas

σ (L ) (Mex. Industry)σ (L i ) (Tex. Industry)σ (L* ) (Mex. Aggregate Manufacturing)σ (L) (Tex. Aggregate Manufacturing)σ (L*i )/σ (Li )σ (L* )/σ (L)
*
i

4.47
na

4.11
2.48

5.50
3.12

2.73
1.66

3.09
2.42

0.77
1.16

0.77
1.16

0.77
1.16

0.77
1.16

0.77
1.16

na

1.66

1.76

1.64

1.69

na

0.66

0.66

0.66

0.66

Notes:The table follows the same format as the top portion of Table 1, but uses total employment rather than
production-worker employment. Percent.
n.a. indicates this industry is not available for that state.

16
Table 4: Adjustment in the Maquiladora Industry: Extensive Margins
Number of Employment
plantsper plant(1)(2)

Industry share of

0.376

0.624

aggregate employment(0.163)(0.163)Aggregate employment

0.494

0.506

(0.052)(0.052)

R2

0.303

0.513

N

480

480

Notes:
Columns (1) and (2) show regressions of either the number of plants or employment per plant on total
Mexican manufacturing employment and the industry share of manufacturing employment. The sample isthe four maquiladora industries in Mexico, with data at a monthly frequency from 1996:1 to 2005:12.
Regressions include controls for industry fixed effects, which are not shown. Standard errors (clustered byindustry) are in parentheses.

17

Figure 1: Employment for Production Workers in Mexico and U.S. Offshoring Industries(log values, seasonally adjusted and HP filtered)
Mexico Apparel

US Apparel (NAICS 315)

Mexico Electronic Materials

US Electronics (NAICS 334)

.2

.1

.05
.1

0
0
-.05

-.1

-.1
1996

1998

2000

2002

2004

1996

2006

1998

2000

Date
Mexico Electrical Mach.

2002

2004

2006

Date
US Electrical Mach. (NAICS 335)

Mexico Transport Equip.

US Transport Equip. (NAICS 336)

.1
.1

.05

0

0

-.05

-.1

-.1
1996

1998

2000

2002
Date

2004

2006

1996

1998

2000

2002
Date

2004

2006