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The Annals of Regional Science

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01.03.2006 | Original Paper

Local labor markets in U.S.–Mexican border cities and the impact of maquiladora production

verfasst von: André Varella Mollick, Abigaíl Cortez-Rayas, Rosa A. Olivas-Moncisvais

Erschienen in: The Annals of Regional Science | Ausgabe 1/2006

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Abstract

Shift-share decompositions of employment positions created over 1990–2002 at U.S.–Mexico border cities show that El Paso employment change has been overwhelmingly attributed to national forces, while local and national forces roughly match employment creation at Brownsville. With such fast growing U.S.–Mexico border area as background, we implement time series labor demand models to these cities (El Paso and Brownsville) and compare movements in Mexican maquiladora production against U.S. employment and wages. Cointegration methods confirm that local shocks are more important in Brownsville than in El Paso. Specifically, 10% increases in Juárez maquiladora production lead to increases of 1.21% in El Paso’s government employment and of 0.88% in overall employment. Similar increases in Matamoros lead to gains of 1.59% in Brownsville’s trade, transportation and utilities employment and of 1.41% in overall employment. These results support shift-share findings and are generally consistent with a more diversified industry-mix promoting higher employment creation.

Vorheriger Artikel A time series analysis of U.S. metropolitan and non-metropolitan income divergence

Nächster Artikel Labor and household mobility: efficiency and equilibrium

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Results vary across locations. At El Paso, for example, 16.59% of the total employment change is due to local forces, −10% is due to industry mix, and an overwhelming 93.45% is due to national forces. At Brownsville, 52.39% of the total employment change is due to local forces, none is due to industry mix, and 47.32% is due to national forces. See GAO (2003) and Table 1 below for a summary.

An interesting city pair to study would have been McAllen and Reynosa, which are economically interdependent, very fast growing, and medium sized cities: McAllen’s MSA with 569,000 and Reynosa with 420,000, according to GAO (2003). However, value added data on maquiladora production for the city of Reynosa is incomplete and precludes the monthly time series approach below. We thus focus on the medium sized city pair of Brownsville and Matamoros. A detailed study of the Tijuana-San Diego interdependence is provided by Chang-Hee (2003).

Not reported figures show an inverse relationship between VA in pesos and unemployment rate in the U.S. border cities (U*). This would imply that, as maquiladora production strengthens, U* falls. The same holds for total wages and U* and for average wages (W/L) and U*. Robertson (2000) finds support that wages in the U.S. affect Mexican wages and concludes the border is more integrated with the U.S. than the interior.

Employing location quotients, Cañas (2002) documents that El Paso still has a larger concentration of manufacturing jobs (16%) compared to the nation (14%), despite the fall in manufacturing employment in the 1990s. We do not know of similar studies to Brownsville, which has been referred to as a “diverse region with a major presence in manufacturing, tourism and retailing” (Brownsville Economic Development Council 2004).

The nine original sectors in GAO (2003) match the BLS classification: construction & mining, manufacturing, transportation & public utilities, trade, wholesale trade, retail trade, FIRE (finance, insurance, and real estate), services, and government. In Table 1, we combine wholesale and retail trade into “trade” and add this to “transportation & public utilities” in order to obtain the “trade, transportation & public utilities” employed below.

Conversely, national forces seem to be more important in El Paso as 94.7% of trade, transportation and utilities and 54.8% of government jobs are due to national effects, against 54.3 and 42.4% in Brownsville, respectively.

A more elaborate alternative to justify a reduced form such as Eq. (4) would be to suppose quadratic adjustment costs and solve for profit maximization in order to obtain equilibrium labor demand (L*) as in Hamermesh (1993). Assuming static expectations about wages and prices, the optimal path of employment is described by dL _t=γ[L*−L _t]. If one replaces L* by a linear function that relates L* to X (a vector composed of variables typically present in labor demand studies), one has: ΔL _t=γ’[G(X _t)−L _t−1], of which a representative empirical equation is: L _t=αL _t−1+β X _t+ɛ_t, where α and β are parameters to estimate. This is the equation to be estimated below in first-differenced form by OLS and in levels by cointegration methods.

In case of LG, we also used the wage of manufacturing as the relevant alternative wage. The average weekly earnings paid to production workers in the construction sector are also used as the alternative wage to all sectors (LM, LT, and LG). The results are very similar, which may reflect the fact that the wage series share common trends at the national level.

The NAFTA dummy variable defined as 0 for the years 1990 to 1993 and as 1 for the years 1994 to 2001, has been included in versions of Eq. (4) and altered some of the estimated coefficients. As it did not improve serial correlation, we prefer to benchmark our model without the NAFTA dummy variable. See Gruben (2001) on this approach and Kose et al. (2004) for more general evidence of NAFTA effects.

A natural generalization of Eq. (6) is the vector autoregressions (VAR) framework. In vector form, Z _t= A Z _t−i+υ _t, where Z is the vector of variables that comprises Eq. (6), A is the matrix of coefficients and υ _t is the vector of errors.

We employ the methodologies of Augmented Dickey Fuller (ADF), Kwiatkowski-Phillips-Schmidt-Shin (KPSS), Elliott–Rothenberg-Stock (DF–GLS), and Phillips-Perron (PP). The results are not overwhelmingly supportive of integrated of order one processes (not all four tests support unit roots in the data) but are certainly not supportive of stationary processes. Related work in Brown et al. (1990) finds that state industrial output does not cointegrate with national output in the same sector and that national and regional earnings do not cointegrate as well. These findings appear to contradict Altonji and Ham (1990) for Canada who document the bulk of variability in regional output due to national shocks. Coulson (1999) estimates sector MSA employment adopting the shift-share model.

Hanson (1996) estimates a panel of annual data on the six largest border-city pairs from 1975 to 1989. He finds that a 10% increase in export manufacturing in a Mexican border city leads to between 2.4 and 4.9% increases in manufacturing employment in the neighboring U.S. border city. A 10% increase in Mexican export production leads to an increase in employment by 1.7 to 2.8% in the U.S. border transport industry and 1.4 to 2.4% in the U.S. border wholesale-trade industry. In services, the industry less affected, experiences an employment rise of 1.3 to 1.6%. In his model, industry dummy variables interact with the logarithm of maquiladora value added.

Altonji J, Ham J (1990) Variation in employment growth in Canada: the role of external, national, regional, and industrial factors. J Labor Econ 8(1)Part 2:S196–S236CrossRef

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Brownsville Economic Development Council (2004) Major industries. Brownsville Overview

Cañas J (2002) A decade of change: El Paso’s economic transition of the 1990s. Federal Reserve Bank of Dallas, El Paso Business Frontier 1

Chang-Hee C (2003) Tijuana-San Diego: globalization and the transborder metropolis. Ann Reg Sci 37:463–477CrossRef

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GAO (2003) Mexico’s Maquiladora decline affects U.S. Mexico border communities and trade. United States General Accounting Office

Gruben W (2001) Was NAFTA behind Mexico’s high Maquiladora growth? Econ Financ Rev FRB of Dallas, Third Quarter:11–21

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Hanson G (1996) U.S.–Mexico integration and regional economies: evidence from border-city pairs. (January). NBER Working Paper 5425

Hanson G (2002) The role of Maquiladoras in Mexico’s export boom. University of California-San Diego, manuscript

Johansen S (1988) Statistical analysis of cointegration vectors. J Econ Dyn Control 12:231–254CrossRef

Kose M, Meredith G, Towe C (2004) How has NAFTA Affected the Mexican economy? Review and evidence. (April). IMF Working Paper

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Texas Workforce Commission (2003) Texas labor market review. Labor Market Information Department, April

Vargas L (2001) Maquiladoras: impact on Texas border cities. Federal Reserve Bank of Dallas, June:25–29

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Titel: Local labor markets in U.S.–Mexican border cities and the impact of maquiladora production
verfasst von: André Varella Mollick
Abigaíl Cortez-Rayas
Rosa A. Olivas-Moncisvais
Publikationsdatum: 01.03.2006
Verlag: Springer-Verlag
Erschienen in: The Annals of Regional Science / Ausgabe 1/2006
Print ISSN: 0570-1864
Elektronische ISSN: 1432-0592
DOI: https://doi.org/10.1007/s00168-005-0031-9

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