Labor market integration between northen méxico and southern united states
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Labor market integration between northen méxico and southern united states Labor market integration between northen méxico and southern united states Document Transcript

  • Labor Market Integration between northern Mexico and southern United States: an empirical investigation AbstractIn this paper, the analysis of co-dependence between the US and Mexico labor markets iscarried out by estimating the cyclical component of California’s and Texas’ manufacturingemployment and four US Border Mexican cities through the Hodrick-Prescott filter. Weestimated the smoothing parameter following a calibration technique proposed byGuerrero et al (2001) which allows us to obtain the best linear unbiased estimator of thetrend component. Our analysis suggests that after 1994 there has been greater labormarket integration between Mexico’s northern region and US’ southern region. Thisgreater integration has implied a change in the nature of the short term relationship ofmanufacturing employment between Mexico and the US. The change is also significant onthe relationship between Mexican real wages and US employment.JEL code: E3, J3, O1Keywords: Labor Market Integration, Hodrick-Prescott filter, in bond industry, Vertical FDI,US-Mexico border 1
  • AuthorsWilly Walter Cortez (corresponding author)Departamento de Métodos CuantitativosUniversidad de GuadalajaraPeriférico Norte No. 799. Núcleo los Belenes, C.P.45100, Zapopan, Jalisco, Méxicoe-mail: wcortez@cucea.udg.mxTelephone:33 3640 24 5033 3770 33 00 ext. 5223Fax: 33 3770 33 00 ext 5227Alejandro Islas-CamargoDepartamento de EstadísticaInstituto Tecnológico Autónomo de MéxicoRío Hondo No. 1, Col. Tizapán San Angel, C.P.01000, Del. Alvaro Obregón, México, D.F.,e-mail: 2
  • 1. Introduction Since the mid 80s Mexico’s economy has been undergoing major structural reforms.Both trade and direct investment liberalizations have induced an industrial restructuringwhich has implied the relative growth of some regions and the decline of others. 1 Theseadjustments have also brought changes in regional labor markets. For example, it has beenargued that economic liberalization has had differentiated impact on regional labormarkets; in particular, it has accentuated, and even increased, existing wage differentialsacross regions (Hanson, 2003). Moreover, regions most exposed to trade and overseasdirect investment seems to have obtained wage gains (Meza, 2002). Another finding in recent studies is that Mexico and US’s labor markets have becomeintegrated (Robertson, 2000). Integration within this context means that a given shock inthe US wage rate induces a change in the Mexican wage rate so that the ratio betweenboth wage rates is affected temporarily. After an adjustment period, the initial wagedifferential is restored. Robertson further argues that this integration is even strongerbetween Mexico’s northern border and the US economy. It should be noted that higherintegration does not mean that both economies are moving towards wage convergence atall (Robertson, 2000; Hanson, 2003). In Robertson’s study, market integration is measured by the responsiveness of wagesin Mexico when wages change in the United States. The adjustment mechanism of relativewages is based on the assumption that labor migrates between both countries in response 3
  • to changes in relative wages. Within this framework then, an increase in the relative wageof the United States causes labor to migrate north, which, in turn, induces the relativewages to return to their initial level. It is unclear however how overall labor supply in Mexico is sensible to changes in theUS wage rate, -even for the northern region as Robertson argues. There are no clearmechanisms through which the adjustment takes place. In fact, there are several issuesthat make Robertson’s explanations highly questionable. First, there is the question aboutthe extent to which labor migration to the US affects overall wage rates in Mexico. Second, a key assumption in Robertson’s study is that the decision to migrate to theUS depends on short run variations of the wage differential between both economies.However, even though the main reason behind Mexican workers’ decision to migrate iseconomic, there is a general consensus that migration is a far more complex phenomenonwhere other factors in addition to the relative wage differential also play a role. In fact, astudy carried out by The Mexico/United States Bi-national Study on Migration in 1997 2concluded that migrants from Mexico tend to have lower skill levels, relative both to theUS population at large and other migrant groups. Furthermore, economic sectors thatemploy Mexican migrants tend to seek lower skilled workers paying them low wages (p. iv).The report identifies two types of factors that drive migration: pull and push factors. Therelative weights of these two types of factors have changed over time. Among the pullfactors the study identifies factors like: new employers, labor brokers, cross-border socialnetworks of relatives and friends. The main push factor is the lack of employmentopportunities in Mexico. One of the study’s findings is that push factors seem to have 4
  • become more important since the mid-1980s as a result of recurring Mexican economiccrises and Mexican policies (p. v ). Third, relative wages between Mexico and US seem to respond more to variations ofthe exchange rate rather than to changes in labor mobility between both countries. Ineffect, during 1980-2003 fluctuations in relative wages have been associated to periods ofhigh depreciation of Mexico’s currency. 3 Moreover, overall growth rate of relative wagesduring this 23-year period has been about 0.7%. In other words, besides the fluctuationscaused by changes in the exchange rates, relative wages have remained more or lessstable. Fourth, the hypothesis not only implies that Mexican workers have access toinformation about US labor market conditions but also that although there are restrictionsto labor migration, these are not impediments to massive labor mobility so that relativewages ultimately respond to it. As argued lines above, Mexican labor migration involvesunskilled labor, which would hardly affect Mexican wages. Due to these limitations we propose an alternative approach to assess labor marketintegration between Mexico and US and depart from previous studies in two importantrespects. First, to the extent that Mexico’s northern border region hosts a large number ofUS subsidiaries, whose production levels depend on both US demand as well asinternational demand for these products, we argue that labor demand in this region isclosely tied to the US business cycles. Second, recent advancements in the theory ofMultinational Corporations (MNCs) include the development of models of vertical ForeignDirect Investment (FDI), which explain not only the emergence of foreign subsidiaries butalso the growing importance in the international economy of both intra-firms trade flows 5
  • and intermediate goods trade. We relate the growing importance of vertical FDI to higherlabor market integration of the economies involved. Due to data availability (or rather restrictions) this study focuses on labor marketintegration between northern Mexican cities and the US economy. We consider theemployment and wage rates as time series, which after adjusting for seasonality andoutliers exhibit trend and cyclical components. Further, we evaluate whether there has been any change in the nature of therelationships between both economies. In particular, we divide the period of analysis intwo. The first goes from 1987:01 until 1994:04 and the second includes the years 1995:01 -2003:01. It is argued that 1995 represents a turning point in the Mexican economybecause of several developments: (i) it is the year in which a major financial crisis tookplace with negative effects on the real sectors of the economy and induced furtherchanges in the latter; (ii) the government adopted a flexible exchange rate system whichhas had some effects on the in bond industry; (iii) the North American Free TradeAgreement was in its first year of being implemented. This trade agreement changed thestrategic behavior of many multinational enterprises (MNCs) with strong repercussions onthe nature of its relationship with their subsidiaries. The empirical analysis is carried out by means of the Hodrick-Prescott Filter (Hodrickand Prescott, 1997). Unlike studies that use the Hodrick-Prescott filter however, thesmoothing parameter is estimated through a calibration technique that allows us to obtainthe best linear unbiased estimator of the trend component (Guerrero, et al, 2001). 6
  • The paper is organized as follows. Section 2 presents a brief discussion about thefactors that explain the emergence and evolution of the in bond industry. Section 3, buildsthe case for expecting greater labor market integration between Mexico’s northern borderregion and the US economy. In particular, we stress the role played by the in bond industryin accelerating such a process. Section 4 describes the methodology followed for theempirical analysis. In particular, it presents the basic ideas of the Hodrick-Prescott (HP)filter, the data used and the carries out the cross correlation analysis and estimatesimpulse response functions. It shows the main results for the short run fluctuations andthe long run behavior of employment in both economies. We present some conclusions insection 5.2. Foreign Direct Investment For the last two decades, less developed economies and emerging economies haveshown a renewed interest to attract Foreign Direct Investment (FDI) as a means to sustain,-even accelerate-, their economic growth.4 It is argued that FDI will bring more resources,new technology and management, including novel marketing and distribution techniques.In addition, and to the extent that the new firms have some spillover effects upon thedomestic firms, overall efficiency will further accelerate. However, FDI has some collateraleffects that not all governments are aware of, but that need to be evaluated to obtain acomplete assessment of the likely impacts of FDI on the host country. Higher co-dependence of the business cycles between the home and the host economy is one 7
  • example. Another example is the higher integration of the home and host countries’ labormarkets. Máttar et al (2002) describe some features of FDI in Mexico. First, it increasingly hasbeen concentrated in manufactures: from 49 % during 1981-93 to approximately 63 %during 1994-2000. Second, the maquiladora plants have been the main receptors. Third,and related to the previous point, it has been directed to highly concentrated industries,with strong multinationals’ presence. Fourth, the large majority of the enterprises are ofUS origin: during 1982-1993 about 60 % of the enterprises were from the US, which by theend of 2000 it went up to around 86 %. Fifth, the strong international position of Mexico’sexports is strongly determined by the growth of foreign firms’ export that was evident adecade earlier than NAFTA. The distribution of FDI in Mexico can also be seen geographically. During 1994-2002about 26.7 % of total FDI was directed to all US-Border states5. This percentage diminishesabout 10 points when we exclude Nuevo Leon 6 and declines even further to about 14.2 %on average if we consider only Baja California, Chihuahua and Tamaulipas. 7 The FDIpattern differs somewhat when we exclude Nuevo Leon; in particular, 1997, 1998 and 2000represent years in which FDI in Nuevo Leon followed a different trend than the rest of theBorder States.8 Despite the fact that since the mid eighties the in bond industry has grown faster innon-border regions, a distinctive aspect is that the US border region hosts, on average,more than 70 % of total plants and around 77 % of total maquiladora employment. 9 This is 8
  • the reason why Mexican researchers believe that this region’s economic performancedepends upon the behavior of the maquiladora plants.2.1. Models of Vertical Foreign Direct Investment A formal model of labor market integration is yet to be developed. However, we caninfer the nature of the integration from the strategic behavior of the MNCs. Therefore, thepurpose of this section is to draw some sketches about the factors that explain theemergence and evolution of the in bond industry. We begin with the early propositionsmade by Vernon (1966) and continue with models proposed by Markusen (1984), Helpman(1984), Markusen et al (1996) and Yi (2003). Historically, US firms were the first ones to establish foreign subsidiaries worldwideso that Vernon’s (1966) explanation was based on US firms’ practices during the 1950s and1960s. Vernon’s theory, known as the product cycle hypothesis, argues that to the extentthat both high-income levels and abundance of skilled labor characterized the US market,the latter provided a fertile ground for constant innovations.10 He also argued that overtime, firms would convert new technologies or innovations into common knowledge. Oncethis occurred, firms would transfer the production of such goods to a different location. Inhis view, the emergence of FDI was a US firm’s response to a real or perceivedmonopolistic advantage. When such an advantage was absent, the firm would not bewilling to take the costs and uncertainties associated with the operation of a foreignsubsidiary. He, however, considered that several conditions needed to be fulfilled for the 9
  • establishment of a foreign subsidiary. First, production process would need to be laborintensive; second, that the goods would have to exhibit high price elasticity; third, that theproduction of the goods were not depended on external economies; fourth, that thetechnology of the production process would have become standardized and that theinventories would not become obsolete rather quick; and fifth, that the goods had a highvalue added compared to its transportation costs. These conditions also determine thereasons why less developed economies would not become countries where innovationwould take place: the small size of their domestic markets and their lack of skilled labor. Changes in the international economy made Vernon (1979) to re-evaluate his earlyideas. In particular, the emergence of Europe and Japan as world economies meant thatthere were new markets that could sustain innovations and the emergence of large firmscapable of FDI. Hence, US firms were not longer the only Multinationals (MNC’s) capableof FDI. They now had to compete against European and Japanese firms that wereestablishing foreign subsidiaries even in the US as a means to gain market share in theinternational economy. The flow of direct investment across industrialized countriesbecame the leading type of FDI, as opposed to FDI going from the latter to lessindustrialized economies. Early analyses on MNCs took Vernon’s ideas as a starting point. These studiesanalyzed different aspects of MNCs operations such as their impacts on the patterns oftrade, home and host countries’ welfare, transfer of technology in a rather descriptivemanner. At that time, formal models of trade were incapable of explaining the existenceof foreign subsidiaries. By the mid 1980s, however, Markusen (1984) and Helpman (1984) 10
  • analyzed the existence of foreign direct investment under the presence of increasingreturns to scale (IRS). In effect, while Markusen (1984) relied on multi-plant economies,Helpman’s model (1984) was based on differentiated inputs; in particular, he considered ageneral-purpose input that played a special role in a differentiated product industry. Inboth cases, IRS emerged as the leading cause of trade (intra-firm trade) and in both casesthe firm was able to separate geographically different internal activities. 11 In Markusen’s model, the multi-plant economies are found in firm-specific activitiessuch as R&D, advertising, marketing, and distribution and management services, the so-called “corporate headquarters”, C. Furthermore, these firm-specific activities, C, tend tobe centralized in a particular location, while production activities, F, are geographicallydispersed. A multi-plant firm has some efficiency advantage over a single-plant firmbecause the former avoids duplication in R&D and other activities carried out by “C” that asingle-plant firm would necessarily have to do. A “national” firm becomes multinationalwhen the sector in which it is located exhibits IRS; that is, when the production involves theproduct of two activities: corporate headquarters, C, and factory, F. If increasing returns inthe sector are weaker than the effects of factor intensity, then the “national” firm wouldmaintain plants in both countries i.e., would become MNC’s. A major drawback of themodel however is that it cannot predict the direction of trade; that is, cannot predict whichcountry ends up with the corporate activities, C, and which one with the productionactivities, F. All that can be said is that activities C will be carried out in the homecountry.12 11
  • Helpman (1984), on the other hand, describes the conditions under which firms findit desirable to establish foreign subsidiaries so that trade patterns can be induced fromsuch a decision. Firms produce a single-good and because they maximize profits theirlocation choices are cost minimizing. Contrary to Markusen’s model, here MNC’s emergeas a result of the tendency of factor price to differ across countries. 13 The IRS sectorproduces differentiated products, while the CRS sector produces a homogenous product. For a while, models about FDI explained either horizontal FDI or vertical FDI but notboth of them at the same time (Markusen, et al 1996). Horizontal MNCs are those multi-plant firms that produce the same product in several countries; substituting internationaltrade for international production. The main purpose of the MNCs in this case is topenetrate a foreign market protected by high tariffs or high transport costs. VerticalMNCs, on the other hand, separate their productive process geographically, takingadvantage of differences in relative factor price across countries. In this case, the objectiveis not to penetrate the host’s market but rather use it to reduce overall costs ofproduction. The first type of models were relevant to explain FDI taking place in advanceindustrialized economies, whereas the second type was more relevant to less developedeconomies. Recent studies about MNCs have provided new insights about the relativeimportance of vertical FDI with respect to horizontal FDI and its role in the impressivegrowth of trade flows that cannot be explained by trade liberalization alone (Hanson et al,2001; Hanson et al, 2003; Braconier, et al, 2002; Yi, 2003). For example, Hanson et al(2003b) show that throughout the nineties US MNCs sent a growing part of their 12
  • production to their subsidiaries through intermediate exports that need further processing.They also show that employment in subsidiaries located in non-OECD countries -i.e., Asiaand Latin America- grew faster than in subsidiaries located in OECD countries, indicatingdifferences in the expansion strategy followed by the MNCs in both groups of countries. In the light of the mounting evidence about FDI, Markusen et al (1996) modify someassumptions present in Markusen (1984) to provide a comprehensive explanation of FDI.In particular, differences in labor’s skills and relative factors endowments. In this model,the firm would choose between horizontal and vertical FDI depending on differences in:relative factor endowments across countries, trade restrictions in the form of higher costs,and market size of the countries involved. The firm’s decision would maximize its overallprofits. Their model assumes that there are two countries, two goods, -one of which exhibitsIRS, X and the other CRS, Y-, two factors of production, -skilled and unskilled labor-.Production of good X uses skilled labor intensively relative to the other good, Y. There arethree types of firms, –nationals (which are one-plant firms), horizontal multinationals(which are two-production plant firms and which locate their headquarters in one countryand each of their production plants in each country), and vertical multinationals (whichlocate their headquarters in one country and their production plants in the other country).Operations of the headquarters require skilled labor, among which we find Research andDevelopment (R&D). Fixed costs of the headquarters use both skilled and unskilled labor,whereas production plant requires only unskilled labor. Within the model, the MNCs candecompose the increasing returns sector, X, into two separate activities: headquarters and 13
  • final production. Headquarters is intensive in skilled labor, more so than the CRS sector, Y.Final production activities are intensive in unskilled labor. Given these assumptions, the model would predict that when country’s differences infactor endowments are moderate, then the country that has relative abundance in skilledlabor exports X. However, if the differences in factors endowments across countries arelarge, then vertical MNCs emerge. Multinational firms would fragment X, and the countrywith the relative abundance of skilled labor will concentrate headquarters activities andthe production would be located in the country with relative abundance in unskilled labor.This decision changes trade direction because now the country with abundant skilled laborwould import the good that is intensive in skilled labor. It should be noted that in this model, vertical multinational dominates productionwhen trade costs are low and the countries differ significantly in relative factorendowments but are of similar size. Horizontal multinational, on the other hand, emergewhen countries are of similar size and relative factor endowments and when the tradecosts are from moderate to large. National firms dominate when the trade costs are lowand the relative endowments are similar, or when trade costs are moderate, relativeendowments are similar and the countries differ significantly in size. The new evidence about the magnitude of vertical FDI helped reconsider two keyissues in the discussion: the definition of vertical FDI and whether differences in relativefactor costs are more important than differences in relative factor endowments inexplaining vertical FDI (Braconier et al, 2002). In effect, early models considered verticalFDI as the practice where foreign subsidiary exports goods only to headquarters, while the 14
  • evidence suggested that the concept of vertical FDI needed to be extended to include inaddition sales from subsidiaries to third countries and sales to the host country. Thus, thepicture of trade flows explained by vertical FDI is more complex than initially thought. The debate about whether differences in relative factors endowments are moreimportant than differences in relative factors prices to explain the impressive growth oftrade and the increasing relative importance of vertical FDI has also reached a turningpoint. Recent empirical studies give more evidence in favor of the relative factors pricesargument (Hanson, 2003b; Braconier et al 2002). Yi (2003), for instance, builds a modelthat can explain the emergence of vertical and horizontal FDI as a function of laborproductivity. The goods consumed and invested by the two countries is produced insequential stages of production. One of the conclusions of the model is that one countrycan produce goods of a particular stage, while the other would produce the remainingstage goods. Given the two countries’ productivity and their relation with respect to theirrelative wages, each one of them would produce the stage good for which is betterequiped, giving rise to some kind of specialization, but on a particular stage of production.3. Why should we expect increasing labor market integration? A priori it cannot be determined the nature of the labor market integration becausethe latter depends on the role that subsidiary plants plays on the overall strategy of theMNCs. Recent developments in the theory of foreign direct investment establish the 15
  • conditions under which business cycles of two economies (Home and Host countries) arepositively or negatively correlated. From an international trade theory perspective, more integration can be expected tolead to more trade; and more international trade will result in more highly correlatedemployment cycles. But this view, particularly the second part is not universally accepted.For instance, Eichengreen (1992) and Krugman (1993) have pointed out that as tradebecomes highly integrated, countries specialize more in production. By this logic,increasing specialization will reduce the business cycle correlation not increase it.Increased specialization might also result from adopting a flexible exchange rate systemsince it dampens the effects of industry specific shocks (Ricci, 1996). 14 From an international trade theory’s point of view, a trade agreement between twocountries may change the nature of the relationship between both labor markets. If theresulting trade flows were more intra-industry than inter-industry, then one would expectthat employment fluctuations in both countries to become positively correlated. On theother hand, if the resulting trade flows were inter-industry, then employment fluctuationsin both countries go in opposite directions. Short run fluctuations of employment can be expressed in terms of its deviationsfrom its long run trend. Thus, the correlation between short run fluctuations of homecountry (A) and host country (M), v , over time span  and de-trended with method a , canbe denoted by Corr (v, a) A,M , 16
  • Labor market integration can also be seen through the impact of changes in homecountry’s employment on host country’s wage rates. The relationship between changes inhome country’s employment and fluctuations in host country’s real wage rates is less clear,however. For one thing, wage rates result not only from the interplay of labor supply anddemand but also from the institutional settings that regulate wage determination; inparticular, the bargaining power of labor to link their wages to domestic inflation rate andto productivity growth. The association between employment in country A and real wagesin country M would provide a direct indicator about whether trade agreement betweencountries A and M have meant an improvement on the latter’s living conditions.4. Methodology In this section we describe the method followed to obtain the trend and cyclicalcomponents of the series. We then discuss the data source and carry out the empiricalanalysis.4.1 The Hodrick-Prescott Filter In what follows we treat the employment ( Et ) and wage series ( wt ) as time series,which exhibit two components: a trend component, g t , and a cyclical component, ct ;thus, wt  gt  ct . The data have been adjusted for seasonality. To the extent that growth 17
  • accounting gives estimates of the permanent component with errors that are small relativeto the cyclical component, the cyclical component is computed as the difference betweenthe observed value and the trend component ( wt  gt  ct ). The aim is to estimate andextract the components g t and ct . The approach developed by Hodrick and Prescott(1997) minimize the following expression: T T  (wt  g t )    (( g t 1  g t )  ( g t  g t 1)) 2 2 t 1 t 1 Where the penalty parameter  controls the smoothness of the series,  . The largerthe  , the smoother  is. As    , g t approaches a linear trend. In recent yearsseveral authors have criticized the mechanical use of the HP filter because it can generatespurious cycles.15 To avoid such a problem, it has been suggested that when investigatingeconomic fluctuations an important first step is the analysis of their variance toquantitatively assess their relative volatility and contribution to the constitution of someaggregate series. A second step is to investigate their cyclical properties in the frequencydomain by means of spectral analysis.16 The popularity of the HP filter is based on some of its desirable properties, -it is asymmetric filter so that no phase shift is introduced, and it has trend reduction properties,furthermore, it places zero weight at the zero frequency. In fact, compared to a band-passfilter proposed by Baxter and King (1995), the HP filter gives essentially the same results forquarterly data.17 Guay and St-Amant (1997), on the other hand, argue that the HP filter 18
  • performs well in terms of extracting business cycle frequencies of time series whosespectra have a peak at those frequencies. That is, if the series is dominated by highfrequency cycles then the HP filter might provide a good approximation of the unobservedcycle frequencies.18 The HP filter requires previous specifications of the parameter  . This parameterdefines the smoothness of the trend. It depends on the periodicity of the data and on themain period of the cycle that is of interest to the analyst. The parameter does not have anintuitive interpretation for the user, and its choice is considered perhaps the mainweakness of the HP filter. For quarterly data, there is an implicit consensus in employingthe value of  = 1600, originally proposed by Hodrick and Prescott. However, theconsensus disappears when other frequencies of observation are used. For example, forannual data, Baxter and King (1995) recommend the value  =10 because it approximatesa band pass filter that removes from the cycle periodicities larger than 8 years, whileBackus and Kehoe (1992), Giorno et al (1995) or European Central Bank (2000) use thevalue  =100. For monthly data, Dolado et al (1993) propose  =4800, while the populareconometrics program E-viewsTM uses the default value 14400. We follow a methodproposed by Guerrero et al (2001) to find the appropriate value of  that yield consistentand more objective results. These authors suggest an alternative interpretation ofWhittaker graduation that yields the graduated series as the best linear unbiased estimatorof the true series. Through an index called the “index of precision share” attributable tothe time series model, they developed a criteria to help reducing subjectivity whengraduating a time series.19 19
  • 4.2 Data Sources The Mexican cities’ employment and wage data come from the National UrbanEmployment Survey (ENEU). We focus on four cities, -Tijuana, Ciudad Juarez, NuevoLaredo, and Matamoros-, mainly because data for other border cities are not as completeas for these cities. Our analysis is based on workers who received an income for their job. The analysisdoes not include workers who worked less than 16 hours and more than 68 hours duringthe reference week. We also excluded males and females younger than 12 and older than75 years. We only consider workers employed in the manufacturing sector. The data arein natural-logarithms so that changes in the long-term components, gt  gt 1 , correspondto the series’ long-term growth rate. The wage rates refers to hourly wage rate and iscomputed by dividing the monthly labor income by the total number of hours worked in amonth. We used the (quarterly) National Consumer Price Index (NCPI) to deflate nominalquantities, using 1994 as the base year. In the case the worker had more than one job, weconsidered the labor earnings of the primary job to estimate wage rates. We obtained quarterly data for manufacturing employment in California, Texas andoverall US manufacturing employment from the US Bureau of Labor Statistics. The strategyof analysis is to evaluate if employment on the Mexican side is integrated to theirneighboring US States (Tijuana with California, Ciudad Juarez with Texas, Matamoros withTexas and Nuevo Laredo Texas) on the assumption that production in the maquiladoraplants depends on manufacturing output (and hence employment) of these neighboring 20
  • States. An alternative assumption is that production on the Mexican side depends more onoverall US manufacturing production rather than just the southern region’s output. Asshall be argued later on, Mexican manufacturing employment seem more integrated to theregional manufacturing employment rather than to the national manufacturingemployment. Table 1 shows the average employment distribution by main economic sectors for thefour largest cities in the Mexican northern border region; namely, Tijuana, Ciudad Juarez,Matamoros and Nuevo Laredo during the period 1987-2000 (figures are percentages ofeach city’s total employment). As can be observed, in the border region as a whole, abouta third of employed labor is occupied in the manufacturing sector (mainly operatedthrough maquiladora plants).20 In Ciudad Juarez and Matamoros the importance of themaquiladora plants as a source of employment is even greater since they occupy about41.3% and 38.8% of these cities’ labor, respectively. In contrast, its importance in Tijuanaand Nuevo Laredo is much lower than the other sectors: 27% and 23%, respectively. INSERT TABLE 1 The Service sector comes second since it generates more than 27% of the region’stotal employment. Commerce comes third because it occupies about 21% of total regionalemployment. It should be noted that Construction and Transport in Nuevo Laredo occupya fairly significant percentage of employed workers (about 10%). 21 In summary,maquiladora plants constitute a significant portion of the region’s labor demand. 21
  • 4.3 Empirical Analysis: the cyclical component We start with a discussion of employment cyclical components of the Mexican citiesand their respective neighboring US states; thus we obtain the following pairs: Tijuana-California, Ciudad Juarez-Texas, Nuevo Laredo-Texas and Matamoros-Texas. The variability of a series is measured by the sample standard deviations, while theco-variability between the employment cyclical components is measured by their cross-correlations. These measures are computed for two sub-periods: 1987:01-1994:04 (pre-NAFTA) and 1995:01- 2003:01 (NAFTA). This division allows us to analyze the stability ofour indicators over time and to evaluate if there were significant changes in the nature ofthe employment relationship after 1994.22 The first two columns of Table 2 and Table 3 present the variability of manufacturingemployment’s cyclical component before 1995 and after that year. Few results are worthmentioning. First, California’s manufacturing employment became more volatile after1995 compared to the previous one. Texas, on the other hand, became less volatile. Onthe Mexican side, volatility increased except in Nuevo Laredo. Both effects induced thatthe relative volatility of Mexican employment with respect to their respective neighboringUS State increased significantly during the second period in Ciudad Juarez, Matamoros andNuevo Laredo (2nd column in table 2 and table 3). INSERT TABLE 2 22
  • Table 2 and Table 3 also show the cross correlation between employment’s cyclicalcomponent of California- Tijuana, Texas- C. Juarez, Texas- Matamoros, and Texas- N.Laredo, before 1995 and after that year, respectively. It can be observed that before 1995(table 2) Tijuana and Nuevo Laredo show no evidence of correlation with themanufacturing employment in California and Texas, respectively. During the same period,short run fluctuations in employment between Ciudad Juarez and Texas and betweenMatamoros and Texas were strong but negative (-0.409 and –0.577 respectively), that is,employment fluctuations in these Mexican cities were counter-cyclical to employment inTexas; moreover, they were felt first in Ciudad Juarez by almost a year earlier whereas inMatamoros was contemporaneous. INSERT TABLE 3 After 1994, there is a clear change in the (short run) employment relationshipbetween these two regions. First, Tijuana and Nuevo Laredo have become highlycorrelated to their respective US neighboring States. They both show strong pro-cyclicalbehavior, -Nuevo Laredo is contemporaneously correlated, while Tijuana’s employmentfluctuations follow that of California with a one-quarter lag. Second, in the case of CiudadJuarez and Matamoros the change is more dramatic: they moved from being counter-cyclical to pro-cyclical. Here too, the highest correlation occurs with one-lag. There is therefore strong evidence that employment fluctuations in the border regionbecame more synchronized after 1995. We find similar results when using the overall US 23
  • manufacturing employment instead. In all cases, there is a movement towards highersynchronization in the fluctuations and, with the exception of Ciudad Juarez; the positivecorrelation became stronger.23 Our results suggest that fluctuations of manufacturingemployment in these Mexican cities are more correlated to their neighboring US States’manufacturing employment than to the overall US manufacturing employment. Moreover,the highest correlation between employment fluctuations on the Mexican side and USmanufacturing employment occurs when they are contemporaneous. In any event, thereis significant evidence of a dramatic change in the coherence of manufacturingemployment fluctuations in this case as well. It is well known that correlation coefficients do not provide information about causalrelationships between the series under study. For this reason, we estimate the impulseresponse function in order to establish the direction of causality of such changes; inparticular, to determine if the direction is in accordance with the relations established insection 2. In what follows we estimate the 2-variable VAR model and the impulse responsefunction with the following ordering: first US states and then the Mexican cyclicalcomponents. The lag length of the VAR was chosen by sequential reduction using theSchwarz Information Criterion (SIC). Figures (2) through (5) show the impulse responsefunction of one standard deviation shock on the cyclical component of manufacturingemployment in California and its effect on Tijuana’s employment, and of Texas’ on CiudadJuarez, Matamoros and Nuevo Laredo’s respectively, from the 1st to the 12th quarter lag. The impulse response functions show that there is a noticeable change in the patternof response of employment’s cyclical components in the Mexican cities after 1995. On the 24
  • other hand, before 1995 the pattern of adjustment showed an initial negative impact topositive in two cities: Ciudad Juarez (4th – 5th quarters) and Matamoros (1st – 4th quarters)to become insignificant afterwards. In the other two cities there was an insignificanteffect: Nuevo Laredo and Tijuana. After 195 the pattern of adjustment changes: a positiveshock on Texas employment induces a significant positive effect on Ciudad Juarez,Matamoros and Nuevo Laredo’s employment. The significant effect for Ciudad Juarez andMatamoros occurs during the first two quarters, while for Nuevo Laredo is from the 2 nd to4th quarter. A positive shock on California’s employment induces a positive significanteffect on Tijuana’s employment cyclical component on the third quarter. In short, before 1995 cyclical components of Mexican (cities) employment and theircorresponding US neighbors were not synchronized. After then, they becamesynchronized: when manufacturing employment in California and Texas were above theirlong-term trend, manufacturing employment in Mexican cities were also above their long-term trend. When using the overall US manufacturing employment instead, the change inthe pattern of adjustment is also evident. First, in the case of Nuevo Laredo the nil effect(of a shock on the US employment) that existed during the first period became positive andalmost permanent after the 3rd quarter during the NAFTA period. Second, in Ciudad Juarezthe initial positive impact that was observed during the first period and despair after the3rd quarter became positive and almost permanent after the 3rd quarter during the post-1995 period. Third, the contemporaneous positive effect on Matamoros during the firstperiod became positive from the 1st to the 6th quarters, reaching its maximum at the 4thquarter. Finally, the nil impact observed on Tijuana during the first period continued 25
  • during the second one. (See appendix B for details). These results indicate that localMexican employment became positively dependent on the cyclical behavior of overall USmanufacturing employment. INSERT FIGURES 1 - 4 Having determined the degree of integration of the labor market in terms ofemployment, we now assess the impact of changes in US manufacturing employment onMexican wages. Figures (6) through (9) show the impulse-response function of onestandard deviation in California and Texas’ employment on Tijuana, Ciudad Juarez,Matamoros, and Nuevo Laredo’s real wages, respectively. Similar to employment, there is a significant change in the pattern of adjustment ofshort-term real wage between the two periods. Manufacturing wages in Tijuana, forinstance, were barely affected by a shock on California’s employment during the firstperiod. It became positive and declined immediately until becoming insignificant after the4th quarter during the second period. In the case of Ciudad Juarez, during the first a shockon Texas’ employment induced a contemporaneous negative effect on short-term wages.It turned positive from the 2nd to 7th quarter, reaching its maximum at the 3rd quarterduring the second period. Matamoros’ wages, on the other hand, maintained the positiveimpact throughout both periods. The only noticeable change was the increase in themagnitude of the relationship. Finally, in the case of Nuevo Laredo the positive impactremained throughout both periods. 26
  • INSERT FIGURES 5 – 8 Our results suggest that manufacturing employment fluctuations in Mexican citieshave become more synchronized to US manufacturing employment (the results hold whenwe look at state-wide and nation-wide data) after 1994. One contribution of this study isto measure not only the degree of labor market integration between both economies butalso the magnitude of such changes. A possible explanation of such changes is that theyare the result of an ongoing restructuring of the in bond industry in northern Mexico.Table 6 presents the employment distribution by main manufacturing sectors as apercentage of total city’s employment during both periods. We observe that between thetwo periods the main changes in the employment distribution have occurred in theMachinery, Equipment and Metal Products sector. In Ciudad Juarez, Tijuana and NuevoLaredo there is a significant increase in the percentage of workers laboring in that sector.In fact, Matamoros is the only city that does not exhibit such changes. 24 In other words,the region seems to have enjoyed an inflow of foreign subsidiaries that tied Mexican labormarket even more than what previously was; in particular, an increasing number ofmaquiladoras plants are assembling more goods classified as machinery, equipment andmetal products.25 INSERT TABLE 4 27
  • 4.4 Empirical Analysis: Trend Component We now turn to the discussion of the long-term behavior of employment in theseMexican cities and that of California and Texas. As can be observed in Figure 10, prior to1995 although there was a resemblance in their behavior this was rather weak. Althoughafter 1994, there is a movement towards a long-term synchronization of employment inthese Mexican cities. In fact, the behavior of Tijuana’s employment was rather distinctthan the other three cities. This changed significantly after 1994: all four cities movedtoward a greater synchronization of their long term behavior of employment, particularlyamong Tijuana, Ciudad Juarez and Matamoros. INSERT FIGURE 95. Conclusions Since the late eighties and early nineties a key variable in emerging economies hasbeen FDI. It has been recognized as an effective instrument not only for transferringtechnology to host economy but also for increasing the amount of trade flow amongcountries. One of the less known impacts of FDI on the host country is the degree to whichit encourages labor market integration between the host and the home countries. The literature on FDI identifies two types of FDI: horizontal and vertical. They eachrespond to a particular set of variables and play a specific role within the overall strategy ofthe MNCs: It is a fact that the type of FDI coming to Mexico is of the vertical type; that is, 28
  • investment that responds to differences in relative factor prices between the home andhost countries. Some authors have argued that trade liberation in general and trade agreements inparticular which accelerate the degree of economic integration among countries could alsoinduce a greater coherence among countries’ business cycles. In this respect, one wouldnot be surprised to find higher labor markets integration. Our argument however is thatlabor market integration caused by vertical FDI is more direct than integration induced byincreased trade flows. The analysis of co-dependence between the US and Mexico labor markets wascarried out by estimating the cyclical component of California, Texas and overall US’manufacturing employment and of four US-border Mexican cities through the Hodrick-Prescott filter. We measured labor market integration in two ways: (1) estimating thecross-correlation of manufacturing employment fluctuations between the two regions, (2)calculating the cross-correlation between US manufacturing employment and Mexican realwage. Our analysis suggests that after 1994 there has been greater labor marketintegration between Mexico’s northern region and US’ southern region. This greaterintegration has implied a change in the nature of the short-term relationship ofmanufacturing employment between Mexico and the US. The change is also significant onthe relationship between Mexican real wages and US employment. We also foundevidence that the long-term behavior of employment also changed unmistakably. Previousto 1995, the trend component of Mexican employment had different behavior. After 1994there is movement toward a greater parallelism in their long –term behavior. That is, we 29
  • observe that there has been a smooth movement towards a state in which theirdifferential growth rates remain constant. One of the most important policy implications of our results is that to the extent thatthe host economy’s labor market outcomes (i.e., employment and wage rates) depend onthe performance of home economy, its labor market policies alone might becomeineffective. Much of the labor market outcome would depend on the decisions that parentfirms would take regarding production in the receiving country. ReferenceAguayo, Francisco and Carlos Salas-Páez, “Reestructuración y dinámica del empleo enMéxico, 1980-1998”, Región y Sociedad, Vol. XIV, Num. 25, 2002, pp. 3-62.Backus David K. and Kehoe, Patrick J. “International Evidence on the Historical Properties ofBusiness Cycles”, The American Economic Review, 82, 1992, pp. 864-888Barajas, E. María del Rosio, Araceli Almaraz, Jorge Carrillo, Oscar Contreras, Alfredo Hualde,Carmen Rodríguez. “Industria Maquiladora en México: Perspectivas del AprendizajeTecnológico-Organizacional y Escalamiento Industrial”, unpublished paper, El Colegio de laFrontera Norte, February, Tijuana, Baja California, México, 2004.Baxter Marianne and Robert G. King, “Measuring Business Cycles: Approximate Band-PassFilters for Economic Time Series”, Review of Economics and Statistics 81, 1995, pp.575-593.Bendesky, Leon, Enrique de la Garza, Javier Melgoza, Carlos Salas, “La IndustriaMaquiladora de Exportación en México: Mitos y Realidades”, unpublished paper preparedfor the Instituto de Estudios Laborales, July, 2003.Binational Study on Migration, “Migration between Mexico and the United States”,, 1998.Braconier, Henrik, Pehr-Johan Norbäck, and Dieter M. Urban, "Vertical FDI Revisited",Centro Studi Luca dAgliano Development Studies Working Paper No. 167, 2002. Availableat SSRN: or DOI: 10.2139/ssrn.347943. 30
  • Cogley, Timothy and J. N. Nason, “Effects of the Hodrick-Prescott filter on Trend andDifference Stationary Time Series, Implications for Business Cycle Research”, Journal ofEconomic Dynamics and Control, Vol. 19, 1995, pp. 253-278.Dolado, J. J., M. Sebastián,, J. Vallés, “Cyclical Patterns of the Spanish Economy”,Investigaciones Económicas, XVII, 1993, pp. 445-473Eichengreen, Barry “Should the Mastricht Treaty be Saved?”, Princeton Studies inInternational Finance, No. 74, Princeton University, December, 1992.Encuesta Nacional de Empleo Urbano, ENEU, Bases de Datos, Instituto Nacional deEstadística, Geografía e Informática, Aguascalientes, quarterly data 1987:01-2003:01.European Central Bank, Monthly Bulletin, October, 2000.Giorno, C., P. Richardson, D. Roseveare, and P. Van den Noord, “Estimating PotentialOutput., Output Gaps and Structural Budget Balances”, Working Papers, 152, OECDEconomics Department, 1995.Granger, Clive W. The Typical Spectral Shape of an Economic Variable”, Econometrica, Vol.34, 1966, pp. 150-161.Guay, A. and P. St-Amant, “Do the Hodrick-Prescott and Baxter-King Filters provide a goodapproximation of Business Cycle”, Working Paper No. 53, August 1997, Center for Researchof Economic Fluctuations and Employment,(CREFE), University du Québec à Montréal,1997.Guerrero, Víctor. M., Rodrigo Juárez, and Pilar Poncela. “Data graduation based onstatistical time series methods”. Statistics & Probability Letters 52, 2001, pp. 169-175Hanson, Gordon; Raymond J. Mataloni Jr.; Mathew J. Slaughter “Expansion Strategies of USMultinational Firms”, NBER Working Paper No. 8433, August, 2001.Hanson, Gordon; Raymond J. Mataloni Jr.; Mathew J. Slaughter “Vertical ProductionNetworks in Multinational Firms”, National Bureau of Economic Research (NBER), WorkingPaper No. 9723, May, 2003.Hanson, Gordon “What has Happened to Wages in Mexico since NAFTA? Implications forHemispheric Free Trade”, National Bureau of Economic Research (NBER), Working Paper9563, March, 2003.Harvey, A. C. and A. Jaeger, “Detrending, Stylized Facts and the Business Cycle”, Journal ofApplied Econometrics, Vol. 8, Nos. 3, July-Sept, 1993, pp. 231-247. 31
  • Helpman, Elhanan “A Simple Theory of International Trade with MultinationalCorporations”, Journal of Political Economy, Vol. 92, No. 3, 1984, pp. 451-471.Hodrick, Robert J. and Edward C. Prescott, “Postwar U. S. Business Cycles: An empiricalinvestigation”, Journal of Money, Credit and Banking, Vol. 29, No. 1, 1997, pp. 1-16Katz, Isaac, “La apertura comercial y su impacto regional sobre la economía mexicana”,Miguel Ángel Porrúa, ITAM, México, 1998.Krugman, Paul, “Lessons of Massachussets for EMU” en Giavazzi, F. and Torres, F. editors,The Transition to Economic and Monetary Union in Europe, Cambridge University Press,New York, 1993.Markusen, James “Multinationals, Multi-Plant Economies and the Gains from Trade”,Journal of International Economics, Vol. 16, No. 3 / 4 (May), 1984, pp. 205-224Markusen, James; Anthony J. Venables; Denise Eby Konan; Kevin H. Zhang “A UnifiedTreatment of Horizontal Direct Investment, Vertical Direct Investment, and the Pattern ofTrade in Goods and Services”, National Bureau Economic Research (NBER), Working PaperNo. 5696, August, 1996.Máttar, Jorge; Juan C. Moreno-Brid,; Wilson Peres, “Foreign Investment in México afterEconomic Reform”, Estudios y Perspectivas # 10, Economic Commission for Latin Americaand the Caribbean (ECLAC), United Nations, Mexico, July, 2002.Meza, Liliana “Desigualdad salarial en México en el periodo 1988-1998: un análisisregional”, Serie Documentos de Investigación, Departamento de Economía, UniversidadIberoamericana, SOO – 16, Diciembre, 2002.Moran, Theodore H. “Inversión Extranjera Directa y Desarrollo” Oxford University Press.México D.F, México, 2000.Ricci, Lucas A. “Exchange rate regimes and location”, Konstanz University, mimeo, 1996.Robertson, Raymond “Wage Shocks and North American Labor Market Integration”, TheAmerican Economic Review, Vol 90, Num. 4, September, 2000, pp. 742-764.Süssmuth, Bernd, Business Cycles in the Contemporary World, Physica-Verlag, New York,2003.Vernon, Raymond, "International Investment and International Trade in the Product Cycle,"Quarterly Journal of Economics vol. 82 No. 2, 1966, pp. 190-207 32
  • Vernon, Raymond “The Product Cycle Hypothesis in a New International Environment”,Oxford Bulletin of Economics and Statistics, Vol. 41, November, No 4, 1979, pp. 255-267.Yi, Kei-Mu, “Can Vertical Specialization Explain the Growth of World Trade?” Journal ofPolitical Economy, Vol. 111, February, 2003, pp. 52-102. 33
  • Table 1: Average Employment Distribution, 1987-2000 Ciudad Nuevo Border Juarez Tijuana Matamoros Laredo Region Manufacturing 0.413 0.271 0.388 0.236 0.329 Commerce 0.197 0.259 0.182 0.208 0.212 Service 0.257 0.270 0.262 0.306 0.273 Construction 0.046 0.067 0.079 0.082 0.068 Transport 0.033 0.050 0.042 0.106 0.057 Note: the figures do not add up to one because the table omits workers employed in Mining, Agriculture and other sectors. Source: National Survey of Urban Employment (ENEU), 1987:01-2000:04. Table 2: SD and CC between US Border Mexican cities and California and Texas: 1987-1994 Standard Standard Cross Correlation deviation deviation (%) relative to CA & TX ME rt 4 rt 3 rt 2 rt 1 rt rt 1 rt  2 rt 3 rt  4 CA ME 1.48 Tijuana 5.74 3.87 0.082 0.119 0.100 0.100 0.039 0.098 0.030 -0.060 -0.145 TX ME 2.11 C. Juárez 8.09 3.83 -0.409* -0.396* -0.405* -0.335* -0.242 -0.107 0.032 0.154 0.219 Matamoro 8.37 3.96 -0.082 -0.236 -0.431* -0.522* -0.577* -0.561* -0.511* -0.426* -0.334* s 11.09 5.25 0.101 0.091 0.003 -0.037 -0.107 -0.187 -0.190 -0.124 -0.070 N. Laredo * Coefficient different from cero at 95% Table 3: SD and CC between US Border Mexican cities and California and Texas: 1995-2003 Standard Standard Cross Correlations deviation deviation (%) relative to CA & TX ME rt 4 rt 3 rt 2 rt 1 rt rt 1 rt  2 rt 3 rt  4CA ME 2.01Tijuana 6.53 3.24 0.023 0.168 0.267 0.377* 0.416* 0.434* 0.415* 0.371* 0.340*TX ME 1.31C. Juárez 8.07 6.16 0.071 0.162 0.359* 0.500* 0.600* 0.618* 0.564* 0.514* 0.489*Matamoros 9.02 6.85 0.050 0.165 0.331* 0.496* 0.618* 0.669* 0.640* 0.584* 0.514*N. Laredo 7.89 6.02 0.078 0.214 0.387* 0.489* 0.497* 0.464* 0.381* 0.392* 0.441* * Coefficient different from cero at 95% 34
  • Table 4: US Border Region: Employment Distribution in Manufacturing Ciudad Juarez Tijuana Matamoros Nuevo Laredo 87-94 95-03 87-94 95-03 87-94 95-03 87-94 95-03Food, Beb. & Tobb. 2.7 2.2 2.9 2.2 2.5 2.2 2.2 1.5Textile 2.6 1.2 0.2 0.2 1.0 0.4 0.1 0.1Clothing 1.4 1.4 1.2 1.9 0.6 2.5 0.7 1.1Chemical Products 1.9 1.1 5.0 2.1 2.6 2.4 2.1 1.2Mach Eq. Met Prod. 26.9 35.4 10.2 17.0 29.2 28.0 13.3 16.0Total 35.4 41.3 19.5 23.4 35.9 35.4 18.5 20.0 Source: ENEU, several years. Figure 1. IR function and error band for California-Tijuana, (employment-employment) (a) period 1987-1994 and (b) period 1995-2003. (a) (b) 0.016 0.027 0.012 0.018 0.008 0.009 0.004 0.000 0.000 -0.009 -0.004 -0.018 -0.008 -0.012 -0.027 0 2 4 6 8 10 0 2 4 6 8 10 35
  • Figure 2. IR function and error bands Texas-Ciudad Juarez (employment-employment), (a) period 1987-1994 and (b) period 1995-2003. (a) (b) 0.032 0.021 0.024 0.018 0.016 0.015 0.008 0.012 0.000 0.009 -0.008 0.006 -0.016 0.003 -0.024 0.000 -0.032 -0.003 0 2 4 6 8 10 0 2 4 6 8 10Figure 3. IR function and error bands Texas-Matamoros (employment-employment), (a) period 1987-1994 and (b) period 1995-2003. (a) (b) 0.012 0.030 0.006 0.025 -0.000 0.020 -0.006 0.015 -0.012 0.010 -0.018 0.005 -0.024 0.000 -0.030 -0.005 -0.036 -0.010 0 2 4 6 8 10 0 2 4 6 8 10 36
  • Figure 4. IR function and error bands Texas-Nuevo Laredo (employment-employment), (a) period 1987-1994 and (b) period 1995-2003. (a) (b) 0.03 0.040 0.032 0.02 0.024 0.01 0.016 0.00 0.008 -0.01 0.000 -0.02 -0.008 -0.03 -0.016 0 1 2 3 4 5 6 7 8 9 10 11 0 2 4 6 8 10Figure 5. IR function and error bands California-Tijuana (employment- wages), (a) period 1987-1994 and (b) period 1995-2003. (a) (b) 0.010 0.035 0.005 0.030 0.000 0.025 -0.005 0.020 -0.010 0.015 -0.015 0.010 -0.020 0.005 -0.025 -0.030 0.000 -0.035 -0.005 0 2 4 6 8 10 0 2 4 6 8 10 37
  • Figure 6. IR function and error bands Texas- C. Juarez (employment-wages) (a) period 1987-1994 and (b) period 1995-2003. (a) (b) 0.02 0.030 0.025 0.01 0.020 0.00 0.015 -0.01 0.010 -0.02 0.005 0.000 -0.03 -0.005 -0.04 -0.010 -0.05 -0.015 0 1 2 3 4 5 6 7 8 9 10 11 0 2 4 6 8 10Figure 7. IR function and error bands Texas- Matamoros (employment-wages), (a) period 1987-1994 and (b) period 1995-2003. (a) (b) 0.020 0.03 0.015 0.02 0.010 0.01 0.005 0.00 0.000 -0.01 -0.005 -0.02 -0.010 -0.03 0 2 4 6 8 10 0 1 2 3 4 5 6 7 8 9 10 11 38
  • Figure 8. IR function and error bands Texas-Nuevo Laredo (employment-wages), (a) period 1987-1994 and (b) period 1995-2003. (a) (b) 0.027 0.030 0.025 0.018 0.020 0.009 0.015 0.000 0.010 0.005 -0.009 0.000 -0.018 -0.005 -0.027 -0.010 0 2 4 6 8 10 0 2 4 6 8 10 Figure 9: Long Term Component: California, Texas and Mexican Cities Employment long-term trend component 7.75 7.50 7.25 7.00 6.75 6.50 6.25 6.00 1987 1989 1991 1993 1995 1997 1999 2001 2003 ECA ETX ECTJ ECCJ ECMA ECNL1 See for instance, Katz (1998) and Aguayo and Salas (2002).2 The Binational Study Group on Migration (1998).3 Relative wages defined as   ln(wUS )  ln(wMX ) where wUS is the hourly wage rate of electronicssector and w MX is the average hourly rate of Mexico’s maquiladora sector (both are in US dollar). 39
  • 4 Moran (2000) shows that during 1990-1998 the flow of FDI directed to less developed economies went fromUS 24 Billion to US 120 Billion.5 There are six Mexican States that share limits with the US: Baja California, Coahuila, Chihuahua, NuevoLeon, Sonora and Tamaulipas.6 We exclude Nuevo Leon because it actually shares a small border region with the United States which is noa maquiladora center. Nuevo Leon is an industrial state whose capital, Monterrey, is the second largest cityin Mexico.7 To the extent that Tijuana, Ciudad Juarez and Matamoros (located in Baja California, Chihuahua andTamaulipas, respectively) are the oldest and the most important maquiladora centers, we wanted to isolatethe percentage of FDI that was directed to this particular region.8 The sharp decline of the percentage of FDI in all three estimates during 2001 is explained by the purchase ofthe largest Mexican bank by Citibank. This transaction was recorded as a FDI that went to Mexico City.9 It should be noted however that during 1990 and 2003, the annual rate of decline of the region’s share inthe number of establishment and employment in the maquiladora sector were 1.04 and 0.98 percentrespectively (source: INEGI, A strong domestic market was a source of stimulus for the innovating firm, while the abundance of skilledlabor and the technological capabilities allowed US firms to improve new products to the point in which thetechnology becomes standardized.11 Both models have some similarities with regards to the assumptions: they are 2x2x2 models, e i, two-countries (home and host), two-goods (one exhibits CRS and the other one presents IRS), two-factors ofproduction. In Markusen these are capital, K, and labor, L; although in Helpman these are labor, L; and ageneral-purpose input, H. In both models firms maximize profits. In both cases, labor is homogeneous andimmobile across countries.12 This result is in part due to the assumption that both countries have the same factors endowments, marketsize, and tastes and preferences.13 The model assumes away transport costs, tariffs and tax advantages.14 In the case of Mexico, it is worth recalling that at the same time that Mexico signed NAFTA, -whichincreased significantly trade between Mexico and US-, the Mexican government adopted a flexible exchangerate. Thus, it is expected that Mexico has become more specialized in the production of specific goods.15 See, for instance, Harvey and Jaeger (1993); Cogley and Nason (1995); Baxter and King (1995), Süssmuth,(2003), among others.16 Süssmuth (2003) argues that spectral analysis in economics has not been used more often for severalreasons. First, it can be applied only to stationary times series. To the extent that most of economicvariables contain a trend component, the failure to effectively remove it would lead to the “typical spectralshape” reported by Granger (1966). Second, many economic series are so short that classical nonparametricmethods of spectral analysis cannot be successfully used. Third, it emphasizes description rather thantesting. Fourth, methods from the time domain, like cointegration analysis still play a predominant role inapplied business cycle analysis.17 This is untrue however for data with other frequencies (Baxter and King, 1995).18 A preliminary spectral analysis of our employment and wage series suggests that a significant variability ofthe series occur at the business cycle frequencies and thus the use of the HP filter is warranted.19 Due to space restrictions the details are available from the authors.20 It should be noted that there is a debate among Mexican researchers about whether these maquiladoraplants are merely assembly plants or not. Some argue that maquiladora plants in Mexico have evolved intoplants with research and development facilities (see for instance, Barajas et al, 2004). Other researchers notethat although there are one or two plants with R&D capabilities, there is still very little evidence that theentire maquiladora sector is moving towards such a situation (Bendesky et al 2003). In fact, the largemajority of maquiladora plants are still assembly plants. What seems to be technological upgrading in themaquiladora productive process is in reality a reflection of the technological advancement that the differentindustries are going through.21 It should be noted that Nuevo Laredo is the main port of entry/ exit of goods transported by trucks. 40
  • 22 It should be noted however that NAFTA began in January of 1994. Our reasoning for taking 1994:04 as theend point of the first period is that the effects of the trade agreement on wages, if there were any, were notfelt immediately but rather it took a few quarters to be felt.23 The results are available from the authors. They are not included due to space restrictions.24 We did not include the percentage in the other sectors because the changes that occurred in them weremarginal.25 Basically, as a result of the auto-components and the electronics industries. 41