Capital and Labour Mobility and their Impacts on Mexico's Regional Labour Markets

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Capital and Labour Mobilityand their Impacts on Mexico'sRegional Labour MarketsRené Cabral a , André Varella Mollick b & João RicardoFaria ca Tecnológico de Monterrey , Escuela de Graduadosen Administración Pública y Política Pública , GarzaGarcía, NL, Mexicob Department of Economics and Finance , University ofTexas - Pan American , Edinburg, USAc IPED , University of Texas at El Paso , El Paso, Texas,USAPublished online: 27 Oct 2010.

To cite this article: René Cabral , André Varella Mollick & João Ricardo Faria (2010)Capital and Labour Mobility and their Impacts on Mexico's Regional Labour Markets, TheJournal of Development Studies, 46:9, 1523-1542, DOI: 10.1080/00220381003599428

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Capital and Labour Mobility and theirImpacts on Mexico’s Regional LabourMarkets

RENE CABRAL*, ANDRE VARELLA MOLLICK** &JOAO RICARDO FARIA****Tecnologico de Monterrey, Escuela de Graduados en Administracion Publica y Polıtica Publica, Garza

Garcıa, NL, Mexico, **Department of Economics and Finance, University of Texas - Pan American,

Edinburg, USA, ***IPED, University of Texas at El Paso, El Paso, Texas, USA

Final version received November 2009

ABSTRACT This paper studies the effects of capital and labor mobility on real wages acrossMexican states for the period 1997–2006. Employing dynamic panel data methods, we find: (1)strong positive effects on real wages from foreign direct investment (FDI) and from migration;(2) domestic and foreign migration provide similar wage effects; and (3) alternative partitionsindicate that real wages are more sensitive to FDI-related fluctuations across states withrelatively lower wages and migration levels. Overall, these results provide support that real wagesrespond positively to fluctuations in capital flows and labour movements as predicted from thetheory.

I. Introduction

Mexico has been subjected to significant labour and capital mobility over the past 20years. One expected consequence of resources mobility is that real wages acrossMexico should reflect these changes. This paper studies the effects of capital mobilityvia foreign direct investment and labour migration (at national and internationallevels), on real wages across Mexican states for the period of the ‘second wave’ ofmarket liberalisation, 1997–2006. The main contribution of the paper is to examinethe effect of all three types of factor flows simultaneously on a regional level.

Since the mid-1990s, the Mexican labour market has been exposed to significantsupply and demand shocks, first with the start of North American Free TradeAgreement (NAFTA) in January 1994, and then with the devaluation of theMexican peso in December of that year. As a result of NAFTA, Mexico’s total tradeto gross domestic product (GDP) ratio increased from 34 per cent in 1993 to 64 per

Correspondence Address: Andre Varella Mollick, Department of Economics and Finance, University of

Texas - Pan American, 1201 W. University Dr., Edinburg, TX 78539-2999, USA. Email: [email protected]

Journal of Development Studies,Vol. 46, No. 9, 1523–1542, October 2010

ISSN 0022-0388 Print/1743-9140 Online/10/091523-20 ª 2010 Taylor & Francis

DOI: 10.1080/00220381003599428

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cent in 2000. Foreign Direct Investment (FDI) inflows went from US$4.3 billion in1993 to US$10.9 billion in 1994. During 1994–2006, Mexico received more thanUS$217 billion in FDI (totalling around 40% of its GDP). In terms of internationalmigration, following the depreciation of the Mexican peso, the net outflow of peoplewent from 412,000 in 1993 to 625,000 by the year 2000.1

Economic theory suggests that while FDI inflows increase labour demand,international migration would cause a decline in labour supply; both factors lead tohigher wages. This paper examines this proposition after a period of significantadjustment by the Mexican economy to several macroeconomic shocks. In a sense,our empirical assessment of fluctuations to labour demand and supply is conductedwhen the economy is on its path to economic recovery amid liberalisation of both itsfinancial and trade sectors. Researchers have identified the post-NAFTA years as the‘second wave of trade and financial liberalization’ in Mexico, following the entry tothe General Agreement on Tariff and Trade (GATT) in the mid-1980s as the ‘firstwave’. Feenstra and Hanson (1997) studied the latter period and showed that risinginequality in Mexico is linked to foreign capital inflows. Examples of the ‘secondwave’ are numerous and include, among others, Chiquiar (2008) for changes inindividual wage regressions between 1990 and 2000. Waldkirch et al. (2009) study theMexican manufacturing industry and find a small but positive and significant effectof FDI on employment.2 A few other papers investigate a longer time span thatincludes both waves, such as Robertson (2005) for absolute wage convergence from1982–2002 and Mollick (2008) on relative wages for 1987–1995 and 1994–2007.To illustrate the development of real wages in Mexico, we observe in Figure 1 the

path of minimum real wages and manufacturing industry real wage indices since1980. The dissimilar pattern of both real wage measures before and after 1994 isevident. Minimum real wages have declined steadily since 1981, with a short periodof stability during 1992–1994. Manufacturing real wages seem a lot more consistentwith the business cycle. They started to decline in 1982, after a significantdepreciation of the Mexican peso, and recovered six years latter in 1988, reaching

Figure 1. Real wage and minimum wage behaviour. Source: Calculated with data from Bancode Mexico.

1524 R. Cabral et al.

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a peak in 1994. After the depreciation of the Mexican peso in late-1994,manufacturing wages declined 22.5 per cent in the subsequent two years but startedtheir recovery in 1996, moving up to reach levels similar to those of 1994 by 2003. Athird real wage measure presented in Figure 1 (available only since 1997) is the dailyaverage real wage for workers registered in the Mexican social security system.3

Along with the manufacturing sector, this broader measure of the real wage shows amore significant recovery of wages with an annual average growth rate of 2.3 percent between 1997–2006. We argue in this paper that this observed recovery of realwages was related to FDI and migration shocks affecting the Mexican economy sincethe second part of the 1990s.

Previous studies have shown some evidence regarding the effects of FDI on realmanufacturing wages. Brown et al. (2004) and Lipsey (2004) review the empiricalliterature on the effect of multinational firms on wages and consistently find thatforeign-owned firms pay higher wages than local firms. More recently, some studieshave challenged this evidence. Heyman et al. (2007) studying employer–employeedata for the Swedish manufacturing sector show that foreign-owned firms pay higherwages than domestic firms but they find no evidence that foreign firms pay higherwages for identical workers. They suggest that higher payments are caused bydifferences in workers and firms’ characteristics. They also find that the premiumpaid by foreign-owned firms is smaller than in previous studies, employing moreaggregated data. Moreover, in the case of firm takeovers, they find no effect or evennegative effects on wages.

The effects of FDI on more aggregate real wages, rather than manufacturing realwages, have been also explored in the literature. A recent example is Ge (2006) whoemploys a panel of Chinese cities to examine the effect of FDI on urban real wagesfinding that foreign capital inflows have a significant positive effect on real wageswhile controlling for other city characteristics. Axarloglou and Pournarakis (2007)examine the effects of FDI on employment and wages in manufacturing employing asample of US states. They find that foreign capital in manufacturing has a weakeffect on employment or wages. The effects of FDI, however, depend on the industrycomposition of those foreign capital inflows. For specific subgroups of industries, theeffects of FDI have been beneficial for local labour markets.

This paper also pays attention to labour supply shifts through state-to-statemigration or through international migration. We use a new dataset at the state levelmade publicly available by CONAPO, the Mexican government national council ofpopulation. This dataset provides us with net outflows or inflows of people from orinto each of the 32 Mexican states, as well as with domestic and foreign migrationrates (outflows minus inflows over total population).4 In a paper close in nature toours, Robertson (2005) analyses the effects of FDI (proxied by maquiladoraestablishments), trade and migration (proxied by border enforcement) on labourmarket integration using data for six urban areas in Mexico and the United States.He finds that trade and FDI have positively contributed to the integration of thelabour market between the two countries but the increase in border enforcement, aproxy for migration, has negatively affected wages in Mexico. A number of otherstudies have explored the effects of migration on real wages in Mexico. Hanson(2004) uses census data for 1990 and 2000 to examine the effects of trade andinvestment on Mexico’s wages structure following NAFTA. He finds that wage

Mexico’s Regional Labour Markets 1525

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differences between skilled and unskilled labour in Mexico have increased due to thedissimilar access to trade, foreign investment and opportunities for migration to theUnited States. Also employing census data, Aydemir and Borjas (2007) observe thatMexican emigration rates are relatively higher for workers in the middle of the skilldistribution, making the relative wage of workers in that section of the distributionalso higher. This has, however, reduced the relative wage of the workers at thebottom of the distribution: ‘despite the large scale migration of low skill workersfrom Mexico to the US, the wage of the low-skill workers in Mexico may have fallen’(Aydemir and Borjas, 2007: 666).Despite the large amount of literature that assesses the effects of greater openness on

Mexico’s labour market, little is yet known about the impact of FDI and migration atthe subnational (state) level. It is well known that inequality across Mexico’s regions issignificant – see Sanchez-Reaza and Rodrıguez-Pose (2002) and Chiquiar (2005). It isexpected that shocks to labour demand and labour supply would affect real wagesdifferently across regions. Moreover, FDI inflows might put in place additionaldynamics by increasing the rate of domestic migration to those states that attract morecapital flows, thus requiring additional labour force. Aroca and Maloney (2006),however, suggest that this might go the other way around and foreign investment andtrade reduce the incentives to migrate. Due to these complex dynamics, additionalresearch is required in order to evaluate whether Mexico’s second liberalisation wavehas had a positive or negative impact on subnational living standards.This study examines the effect of market liberalisation on Mexico’s real wages

across its 32 subnational entities for the period 1997–2006. We pay particularattention to the effect of FDI and migration shocks on real wages, employing staticand dynamic panel data methods with checks for robustness. Section II describes thedataset, presents some descriptive statistics and political maps which describethe geographical patterns of real wages, FDI and migration. Section III contains thetheoretical foundations underlying our empirical model and Section IV examines thedeterminants of real wages across Mexican subnational states. Finally, Section Vprovides some concluding remarks.

II. Data

Data was compiled from different government agencies. Wages were taken fromMexico’s ministry of employment (1997–2006 daily average state wages data areavailable from Secretaria del Trabajo y Prevision Social). These data correspond toaverage daily wages reported by the employers to the Mexican Institute of SocialSecurity (Instituto Mexicano del Seguro Social) regarding permanent employeesregistered in rural and urban areas. Foreign Direct Investment (FDI) data wereobtained from the Ministry of Economy (Direccion Nacional de InversionExtranjera, Secretarıa de Economıa).International migration rates, domestic migration rates and state population

figures were gathered from the National Population Council (CONAPO, ConsejoNacional de Poblacion).5 GDP per capita, our proxy for labour productivity, wasconstructed based on national accounts statistics provided by INEGI (InstitutoNacional de Estadıstica Geografıa e Informatica) and population figures wereobtained from CONAPO. Ideally, the period covered by this analysis would include


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some of the pre-NAFTA years. Nonetheless, the availability of state wages statisticsrestricts our analysis to the period 1997–2006.

Table 1 shows some descriptive statistics for our data set. Average wages aremeasured in daily real pesos in 1993 prices. The highest average real wage is observedin the capital of Mexico, Distrito Federal (id #9), at 54 pesos, followed by thenortheast state of Nuevo Leon (id #19) at 42.9 pesos. Average output per capita isalso the largest in these two states, which is expected given that wages should berelated to the productivity of labour. The lowest average real wages is observed inDurango, only 26 pesos, followed by Zacatecas and Chiapas, with 26.4 and 27 pesos

Table 1. Descriptive statistics

Id StateRealWage

Outputper capita

FDI toGDP ratio

Internationalmigration rate

Domesticmigration rate

W Y fdi im dm

1 Aguascalientes 33.6 17,918 1.2 0.44 70.492 Baja California 39.0 19,208 5.1 70.30 71.113 Baja California Sur 37.0 18,397 4.3 0.33 71.574 Campeche 39.7 23,185 0.2 0.39 70.225 Chiapas 27.0 6,323 0.0 0.22 0.356 Chihuahua 34.9 20,910 3.5 0.68 70.227 Coahuila 34.8 20,726 1.0 0.39 70.028 Colima 32.6 15,123 0.3 0.54 70.559 Distrito Federal 54.0 36,455 8.7 70.05 0.9310 Durango 26.0 12,912 0.9 0.96 0.1811 Guanajuato 30.5 11,313 0.6 1.17 70.0512 Guerrero 30.8 7,720 0.2 1.20 0.4113 Hidalgo 31.6 8,965 0.1 1.05 70.2714 Jalisco 35.7 14,487 1.6 0.60 70.0215 Mexico 40.8 11,752 1.8 0.30 70.3116 Michoacan 31.9 8,615 0.2 1.66 0.0817 Morelos 37.1 13,335 1.2 0.84 70.3918 Nayarit 27.6 8,801 1.6 1.35 70.2619 Nuevo Leon 42.9 26,083 5.1 0.30 70.2820 Oaxaca 29.4 6,213 0.0 1.12 0.2321 Puebla 35.7 10,004 2.3 0.45 70.0122 Queretaro 42.1 17,277 1.4 0.30 70.6723 Quintana Roo 31.8 21,801 1.3 70.79 71.7824 San Luis Potosı 33.1 11,085 1.0 0.90 0.0625 Sinaloa 28.2 11,829 0.3 0.93 0.3226 Sonora 31.4 17,952 1.5 0.53 70.1027 Tabasco 31.4 8,910 0.7 0.42 0.3928 Tamaulipas 36.1 15,892 2.2 0.58 70.4929 Tlaxcala 32.2 7,935 0.8 0.33 70.2730 Veracruz 32.5 8,753 0.2 0.58 0.3731 Yucatan 27.6 11,655 0.5 0.01 70.0732 Zacatecas 26.4 8,690 0.2 1.51 0.11

Average 33.9 14,382.0 1.6 0.59 70.18Correlation (W/P, X) 0.77 0.8 70.45 70.08

Notes: Migration rates are calculated as the difference between outflows and inflows of peopleover total population. Correlations are calculated between real wage averages and its cross-sectional average determinants.


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respectively. The lowest output per capita is observed in the southern states ofOaxaca, Chiapas and Guerrero. In our sample, the relation between real wages andoutput per capita is positive and strong with a correlation coefficient of 0.77. A clearpattern of real wages and their geographical location can be observed in Figure 2.The political map in Figure 2 clearly shows how states with higher than average realwages are concentrated along the border with the United States and at the centre ofMexico. Sonora, the only northern border state that does not observe a higher thanaverage real wage, is only 2.5 pesos below the national average. Meanwhile,Campeche is the only southern state with higher than average real wages and this isdue to the presence of the state company PEMEX. The company concentrates asignificant part of its extraction of oil and gas from the Gulf of Mexico in this state.For the period observed, FDI represents on average around 1.57 per cent of GDP

across all 32 states. The largest recipient of FDI is the capital of Mexico, DistritoFederal, 8.75 per cent, followed by the northern border states of Nuevo Leon andBaja California, with about 5.1 per cent of their respective GDP each. The stateswith the lowest FDI are the southern states of Chiapas and Oaxaca, followed bycentral state of Hidalgo (less than 0.5% of their respective GDP in all three cases).Figure 3 shows the geographical location of states above and below the averageannual FDI to GDP ratio. The concentration of the highest receivers of FDI alongthe northern border and the centre of Mexico is evident from this diagram. Apotential problem that might arise from controlling for capital mobility using FDIflows is the correct geographical accountability of investment. FDI can be reported

Figure 2. Geographic location of real wages across Mexican states. Note: Calculated usingdata from the Ministry of Economy taken from National Security System (IMSS).


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and accounted according to the location of a firm’s headquarters and not necessarilyon the state where that productive investment is finally allocated.6

Finally, with respect to migration, in the last two columns of Table 1 we observethe average rates of international and domestic migration. These are calculated asthe outflows of people minus inflows over total population. On internationalmigration, only three states in the country experienced a net inflow of people:Quintana Roo (0.79%), Baja California (0.30%), and the capital of Mexico, DistritoFederal (DF) (0.05%). These states typically receive a considerable amount offoreign immigrants due to tourism and business activities. Among the states withmore migrants abroad are Michoacan (1.66%), Zacatecas (1.51%) and Nayarit(1.35%). The geographical pattern of international migration is shown in Figure 4.States with more than average net migration rates extend all along Mexico fromChihuahua in the northern border to Oaxaca. The correlation between real wagesand international migration is negative (correlation coefficient of –0.45), which is inline with the idea that those states with higher net migration also observe the lowestreal wages. This negative correlation coefficient goes against the theoreticalhypothesis that higher migration leads to a reduction of the labour supply andthus to higher real wages. Indeed, causality could run the other way around and, infact, lower wages can increase the incentives to migrate. Besides, correlation does notimply causation. If the empirical model is not misspecified we are in a better positionto ascertain which of these movements appears to be stronger and how to rationalise

Figure 3.Geographic location of FDI across Mexican states. Note: Calculated using data fromthe Ministry of Economy, FDI National Commission (CNIE).


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the patterns. By not finding serious problems of misspecification in the estimationsbelow, we thus can use the maintained hypothesis that flows of migration and FDIare determinants of real wages.The sample correlation between real wages and domestic migration is also

negative, but with a much smaller value (a correlation coefficient of –0.08). Thegeographical pattern of domestic migration is shown in Figure 5. We observe 10states that are net exporters of labour to other states of Mexico and 22 that are netimporters of domestic labour. Among the main exporters are the capital (Mexico,DF), Guerrero and Tabasco and among the main importers are Quintana Roo, BajaCalifornia Sur and Baja California. The relation between domestic and foreignmigration is positive (correlation coefficient of 0.45) but far from perfect.7 Indeed,shocks to labour supply and demand might play a very important role across thestates of Mexico, contributing to move wages away from its normal level, as given bythe marginal product of labour. Consequently, considering the effect of not justforeign but also domestic migration could be useful to control for the effects ofdemand and supply shocks across states over time.

III. The Model

Our model starts from a very simple set-up. Labour demand follows Barrel and Pain(1997, 1999).8 We assume that production in subnational entity i at time t is given by

Figure 4. Geographical location of international migration net flows across Mexican states.Note: Calculated using data from the National Population Council, Ministry of Employment

(CONAPO).


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a constant returns to scale Cobb-Douglas production function which depends oncapital (K), labour (L), and a productivity factor (A):

Yit ¼ AitKgitit L

sitit

ð1Þ

where capital and labour elasticities, git and sit, are entity and time varying.Obtaining the marginal productivity of labour @Yit

@Lit

� �and equalising it to the real

wage Wit

Pt� wit, we obtain the labour demand:

wit ¼ sitAitKgitit L

sit�1it ð2Þ

Labour supply is a positive function of real wage and a negative function of netmigration (M):

Lit ¼ S wit;Mitð Þ; Sw > 0;SM < 0 ð3Þ

Capital stock is divided between domestic K, and foreign capital eK. Foreign directinvestment, denoted as I henceforth, enters in our model affecting positively thestock of foreign capital:

~Kit ¼ ~K Iitð Þ ) ~Kit ¼ kIit; k > 0 ð4Þ

Therefore, capital stock is: Kit ¼ kIit þ Kit

Substituting Equation (4) into (2) yields:

wit ¼ sitAitðkIit þ KitÞgitLsit�1it ð5Þ

Rewriting (5) we express labour demand as:

Lit ¼ witðsitAitðkIit þ KitÞgitÞ�1h i1=ðsit�1Þ

ð6Þ

Labor market equilibrium is reached when labour supply equals labour demand,from (3) and (6) we have:

Sðwit;MitÞ ¼ witðsitAitðkIit þ KitÞgitÞ�1h i1=ðsit�1Þ

ð7Þ

Labour market equilibrium (7) determines the equilibrium real wage wit.Total differentiation of expression (7) yields:

dwit ¼½Sðwit;MitÞ�sit�1sit Yit

Lit

Lit

Lsitit

h iðsit � 1Þ½Sðwit;MitÞ��1SM½ddit þ djit� þ gitK

�1it ½kdIit þ dKit�

n o

1� ðsit � 1Þ½Sðwit;MitÞ�sit�2Swsit Yit

Lit

Lit

Lsitit

h i

Note that in (8), net migration was divided between domestic (d), andinternational (j) migration: Mit ¼ dit þ jit. Its total differentiation is:

ð8Þ


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dMit ¼ ddit þ djit. The expression (8) shows that equilibrium real wage is a functionof FDI (I), net migration (M) [or, rather, net international and domestic migration],

output per capita (Y/L), and domestic capital ( K� �

). Equation (8) allows us to assess

the impact of exogenous changes in FDI and migration on real wage.9 The impactof FDI on real wages is:

dwit

dIit¼

½Sðwit;MitÞ�sit�1sit Yit

Lit

Lit

Lsitit

h ikgitK

�1it

� �1� ðsit � 1Þ½Sðwit;MitÞ�sit�2Swsit Yit

Lit

Lit

Lsitit

h i ð9Þ

Note that (sit71)5 0, and the denominator is positive, as a consequence the impactof FDI on real wages is positive.The impact of international migration on real wage is:

dwit

djit

¼½Sðwit;MitÞ�sit�1sit Yit

Lit

Lit

Lsitit

h iðsit � 1Þ½Sðwit;MitÞ��1SM�n o

1� ðsit � 1Þ½Sðwit;MitÞ�sit�2Swsit Yit

Lit

Lit

Lsitit

h i ð10Þ

Note that SM5 0, and the numerator is positive, therefore the impact of netinternational migration on real wage is positive. The same holds true for domesticmigration. It is easy to verify that the impact of domestic migration on real wage isthe same as the right hand side of expression (10).An econometric specification corresponding to (8) is:

oit ¼ bo þ b1iþ b2yit þ b3fdiit þ b4imit þ b5dmit þ eit ð11Þ

where: oit is the log of the real wage, yit is the log of the labour output percapita, bo is a constant, b1i is a state specific effect, fdiit is the ratio of FDI toGDP in each state (which corresponds to Iit/Yit), imit is rate of internationalmigration, dmit is rate of domestic migration, and eit is the stochastic randomcomponent.10 We expect output per capita (yit) to control for productivitydifferences across states under the idea that the more productive states are alsothose that receive higher real wages. Two factors prevent us from including thestock of capital in the econometric specification of Equation (11). First, a controlvariable such as capital stock or the per capita capital stock (K/L) would behighly correlated with output per capita (Y/L), another of our controls. Second,empirically testing for the effect of domestic capital is not feasible as there are noseries of capital stock available for the Mexican states (only 5 year frequency dataon capital stock could be obtained), nor can we separate the stock of capital (atthe state level) into domestic and foreign.From the comparative statics in Equations (9) and (10), we expect coefficients b3

and b4 in (11) to be positive. An extension of the econometric model in (11) includesalso the real exchange rate rerit and lagged real wages wit–1:

oit ¼ bo þ b1wit�1 þ b2yit þ b3fdiit þ b4imit þ b5dmit þ b6rerit þ eit ð12Þ


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This equation takes into account the effect of real wages persistence or stickiness,through the b1-coefficient. Hamermesh (1993) provides reasons from economictheory – through adjustment costs – that justify lagged terms such as those present in(12).11 We would expect that for the period observed the declining rate of inflation inMexico would also lead to wage stickiness and little flexibility of the labour market.We expect the effects of domestic and international migration rates on real wages tobe positive as before; that is, a contraction in domestic labour supply would alsoimply an increase in domestic real wages. A real exchange rate depreciation wouldmake the state economies more competitive if they are heavily engaged in tradeactivities. However, the pass-through effect into prices will negatively affect the valueof the real wage since the price level would go up, pushing down real wages.

A serious problem arises when one wishes to estimate the model in (12) usingordinary least squares (OLS) since the right-hand side contains a lag of thedependent variable which is correlated with the error term even if we assume thatthe residuals are not autocorrelated. Arellano and Bond (1991) developed aGeneralized Method of the Moments (GMM) estimator that solves this problem.Their method takes first differences of Equation (11), removing the industryeffects (b1i), and produces an equation that is estimable using instrumentalvariables. Differentiation of the model eliminates the endogeneity problem thatmight result from the correlation of state-specific effects and the explanatoryvariables on the right-hand side. In addition, endogenous explanatory variablesare instrumented with suitable lags. Blundell and Bond (1998) proposed a modelin which lagged differences are employed in addition to the lags of theendogenous variables, producing more robust estimation in comparison withthe Arellano and Bond (1991) method which turns out to be weak when theautoregressive processes are persistent.

GMM estimation is said to be consistent if there is no second orderautocorrelation in the residuals and the instruments employed are valid. The mostcommon test employed to verify the validity of instruments in this GMM setup is theSargan (1958) test of over-identifying restrictions. We employ the system GMMmodel proposed by Blundell and Bond (1998) to estimate Equation (12).

While the static models do not capture adjustment costs and the dynamicadjustment of wages, they do point out the extent of heterogeneity of cross-sectionunits and may serve as a first approximation to real wages at a regional level. AnAppendix is included to reinforce the major points of the estimation procedureallowing for the simultaneity of wages, FDI, and migration.

IV. Empirical Results

Static Specification

Table 2, columns (a) and (b) presents the estimates of Equation (12) employing staticpanel data methods.12 Column (a) presents the estimates of the model without fixedeffects and columns (b) the estimations including fixed effects. All estimates in Table2, columns (a) and (b) report in parenthesis standard errors which are robust toautocorrelation and heteroskedasticity. For the estimates without fixed effects incolumns (a), output per worker, FDI, domestic migration and the real exchange rate


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seem to be significant and present the expected signs. Only international migrationpresents a non-significant and unexpected sign.For the estimates in column (b), the inclusion of the not reported but significant

state specific fixed effects coefficients eliminates the significant effects on real wages ofour market liberalisation shock variables in the b3 and b5 coefficients: FDI, as well asdomestic migration. Only output per capita, our proxy for productivity, and the realexchange rate, present the expected sign. The coefficient for output per capita islarger than unity in this case, suggesting that a 1 per cent increase in output percapita has a more than proportional effect on real wages. It is possible, however, thatthe relationship between real wages and the regressors in Equation (12) is notprecisely captured because dynamic adjustment is not captured.

Dynamic Estimates

While we are able to deal with autocorrelation and heteroskedasticity problems inour estimates in Table 2, one of the problems we cannot deal with employing staticpanel data methods is that of misspecification. Due to its construction, system GMMestimates are robust to unobserved heterogeneity and endogeneity problems. Themethod employed differentiates first the estimated equation removing state specificeffects. Thereafter, lagged differences and lagged levels are employed as instrumentsfor the level equations.

Table 2. Real wage determinants in Mexico for the post-NAFTA era

wit¼ b0iþ b1wit-1þ b2yitþ b3fdiitþ b4imitþ b5dmitþ b6rertþ eit

Fixed effects System GMM

Coefficient (a) (b) (c) (d)

b1 0.868*** (0.019) 0.878*** (0.022)b2 0.205*** (0.027) 1.096*** (0.058) 0.106*** (0.023) 0.112*** (0.029)b3 2.148*** (0.436) 0.041 (0.249) 0.251*** (0.076) 0.340*** (0.100)b4 70.026 (0.021) 70.001 (0.038) 0.040** (0.017) 0.039* (0.021)b5 0.033** (0.016) 0.038 (0.051) 0.051*** (0.014) 0.045*** (0.013)b6 70.005*** (0.001) 70.003*** (0.000) 70.003*** (0.000) 70.003*** (0.000)b0 1.925*** (0.278) 76.997*** (0.587) 70.327 (0.200) 70.417* (0.229)R2 0.527 0.441Sargan 31.56 (0.293) 25.439 (0.604)AB(1) 74.76 (0.000) 74.034 (0.000)AB(2) 0.30 (0.763) 70.637 (0.524)N 320 260 288 234

Notes: Logarithms are taken on real wages and output per capita. Under fixed effects b0icoefficients are estimates for each state but only a single intercept coefficient (b0) is reportedhere. Under System GMM (SGMM) the fixed effects are eliminated, all that is left is the singleintercept coefficient b0. Columns (a) and (b) report Newey West standard errors robust toheteroskedasticity and autocorrelation. Columns (c) and (d) report first-step SGMMheteroskedasticity robust estimators as proposed by Blundell and Bond (1998). The Sargantest reports that under the null the overidentified restrictions are valid. AB (1) and AB (2)correspond to the Arellano-Bond test for serial correlation, under the null of noautocorrelation. Robust standard errors are reported in parenthesis. The symbols *, ** and*** refer to levels of significance of 10, 5 and 1 per cent, respectively.


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Columns (c) and (d) in Table 2 present the results of the dynamic estimation ofEquation (12). Column (c) includes the complete sample of 32 Mexican states;column (d) excludes the states in the northern border. Heteroskedasticity robuststandard errors are reported in parenthesis. Before discussing the results in detail, itis important to check the appropriate specification of the model. Our system GMMestimators are consistent only if the moment conditions employed are valid. Underthe Sargan test of overidentifying restrictions for the two-step estimations, ourestimates do not reject the null that the instruments employed are valid undercolumns (c) or (d). In addition, moment conditions are valid only if there is nosecond order serial correlation in the residuals. While rejecting the null of no firstorder autocorrelation does not entail that the model is misspecified, rejecting the nullof no second order autocorrelation (and thus of further orders) would imply that themoment conditions are not valid.

All the coefficients in columns (c) and (d) present significant coefficients with theexpected signs and are free from autocorrelation or misspecification problems. Forthe model in column (c), the output per capita coefficient of 0.106 suggests that a 1per cent increase in productivity results in nearly a 0.11 per cent increase in realwages. The FDI to GDP ratio is positive and significant, implying that a 1 per centincrease in the share of FDI relative to GDP results in a 0.25 per cent increase in realwages. Presumably, this effect might be the result of both a larger demand for labour,as suggested by Waldkirch et al. (2009) for the Mexican manufacturing sector, andthe better paid jobs created by foreign-owned firms. International and domesticmigration rates pose significant and positive effects on real wages, with coefficients of0.040 and 0.051, respectively. Finally, as in the static model, the real exchange ratehas negative and significant effects on real wages. We simply argue here that the realexchange rate pass-through to inflation results in lower real wages.

Since according to the descriptive statistics observed in Table 1 states in the northernborder present on average higher wages, FDI flows, lower international migrationoutflows and higher domestic migration inflows, we exclude in Table 2, column (d), thestates of Baja California Norte, Sonora, Chihuahua, Coahuila, Nuevo Leon andTamaulipas from the sample. The results in this column are consistent with those incolumn (c) but the effect of FDI becomes stronger: implying a 0.34 per cent increase inreal wages when there is a 1 per cent increase in the FDI to GDP ratio. The Sargan testand the Arellano-Bond tests also suggest that the identifying restrictions are valid.Output per capita and FDI to GDP ratio coefficients are slightly larger in column (d).This might reflect the fact that the lower GDP per capita and the more FDI deprivedstates have real wages more sensitive to capital inflows and productivity gains.Similarly, international and domestic migration coefficients are slightly smaller and, forthe case of international migration, less significant than for the full sample in column(c). This suggests that the positive effect of migration on real wages is less important forthose states that experience relatively more labour outflows.

Robustness Checks

In addition to taking Mexico’s northern border states out of the sample as done incolumn (d) of Table 2, we check in Table 3 the robustness of our results partitioningthe sample above and below the mean of real wages, international and domestic


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Table

3.Partitionsofthesample

aboveandbelow

themeanin

dynamic

models

oit¼b 0þb 1

wit-1þb 2

yitþb 3

fdi itþb 4

imitþb5

dm

itþb 6

rer tþe it

Realwage

Incomeper

capita

Internationalmigration

Domesticmigration

FDIto

GDPratio

Coeffi

cient

Above

Below

Above

Below

Above

Below

Above

Below

Above

Below

b 00.173

70.270

70.890**

70.586**

70.139

70.271

70.011

0.198

70.623**

70.202

(0.317)

(0.250)

(0.398)

(0.238)

(0.177)

(0.368)

(0.225)

(0.159)

(0.309)

(0.168)

b 10.800***

0.924***

0.779***

0.890***

0.921***

0.819***

0.909***

0.845***

0.819***

0.895***

(0.018)

(0.028)

(0.041)

(0.031)

(0.032)

(0.026)

(0.026)

(0.031)

(0.048)

(0.020)

b 20.082***

0.080**

0.197***

0.130***

0.063***

0.120***

0.056*

0.063***

0.157***

0.083***

(0.029)

(0.034)

(0.049)

(0.036)

(0.022)

(0.039)

(0.029)

(0.014)

(0.038)

(0.021)

b 30.169**

0.583**

0.225**

70.138

70.041

0.264***

0.209

0.227**

0.214***

0.185

(0.070)

(0.251)

(0.112)

(0.210)

(0.282)

(0.058)

(0.132)

(0.109)

(0.066)

(0.286)

b 40.007

0.036**

0.025

0.011

0.061*

0.011

0.034

0.007

0.039*

0.035**

(0.019)

(0.016)

(0.022)

(0.025)

(0.033)

(0.019)

(0.022)

(0.009)

(0.023)

(0.018)

b 50.035

0.042***

0.059***

70.013

0.021

0.055***

70.007

0.021*

0.057***

0.045***

(0.023)

(0.016)

(0.014)

(0.032)

(0.033)

(0.017)

(0.036)

(0.012)

(0.017)

(0.015)

b 670.003***

70.003***

70.003***

70.003***

70.003***

70.003***

70.003***

70.003***

70.003***

70.003***

(0.000)

(0.000)

(0.000)

(0.000)

(0.000)

(0.000)

(0.000)

(0.000)

(0.000)

(0.000)

Sargan

12.781

18.135

13.763

17.571

12.335

18.749

16.851

14.506

9.561

21.821

(0.998)

(0.923)

(0.989)

(0.936)

(0.995)

(0.906)

(0.952)

(0.984)

(0.999)

(0.790)

AB(1)

73.25

73.424

73.4339

73.6352

73.2164

73.5246

73.5304

73.3318

72.9737

73.74327

(0.000)

(0.001)

(0.001)

(0.000)

(0.001)

(0.000)

(0.001)

(0.001)

(0.000)

(0.000)

AB(2)

0.77908

71.142

2.18

70.8786

0.10988

0.39719

70.60434

0.41898

1.838

70.7806

(0.436)

(0.253)

(0.029)

(0.380)

(0.913)

(0.691)

(0.546)

(0.675)

(0.066)

(0.435)

N117

171

162

162

117

171

153

135

90

198

Notes:Logarithmsare

taken

onrealwages

andoutputper

capita.Thetablereportsfirst-step

System

GMM

(SGMM)robustestimators

asproposed

byBlundellandBond(1998).TheSargantest

reportsthatunder

thenulltheoveridentified

restrictionsare

valid.AB(1)andAB(2)correspondto

theArellano-Bondtestforserialcorrelation,under

thenullofnoautocorrelation.Robuststandard

errors

are

reported

inparenthesis.Thesymbols

*,**and***referto

levelsofsignificance

of10,5and1per

cent,respectively.


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migration and FDI to GDP ratio. We are particularly interested in observing theeffects on real wages of FDI demand-related shocks and (international and domestic)migration supply shocks (that is, coefficients b3 to b5). Notice that for all theestimates in Table 3, whenever significant, our shock coefficients present the positiveexpected effect on real wages. The Sargan test and the second order autocorrelationtests suggest that the moment conditions employed in each specification are valid.

Under the columns of real wages, we observe how states with below average realwages are significantly more sensitive to FDI inflows, international and domesticmigration than states with real wages above the mean. Jointly, these results mightsuggest that states with relatively low wages are more sensitive to both supply anddemand shocks to the labour market.

For the partition according to income per capita, the b3 coefficients are higher andstatistically significant only for states with income per capita above average. Theeffect of FDI on wages is larger at higher levels of economic development. The effectof domestic migration on wages is larger for states with higher levels of economicdevelopment. One possibility is that people in higher income states are more skilledand thus attract higher wages when they move searching for better returns. Thiswould be consistent with the results for the 50 Spanish provinces by Mauro andSpilimbergo (1999), who find that highly skilled workers migrate promptly after adecline in regional labour demand, while low-skilled workers drop out of the labourforce or remain unemployed for long periods of time.

Below the international migration columns we also split the sample into thosestates with migration rates above (high migration) and below the average (lowmigration). Comparing the two subsamples, we observe that wages in states withrelatively low international migration (below average) are significantly moreresponsive to FDI-related demand shocks and domestic migration supply shocks.The first result indicates that FDI flows favour those states in which labour is morestable by creating better paid jobs. The second result simply suggests that lowdomestic migration has a higher impact on real wages across those states with lowerinternational migration.

We partition the sample in a similar way for states with domestic migration aboveand below the national average. As in the case of international migration, we observea higher responsiveness of real wages to FDI demand-related shocks across stateswith relatively low domestic migration but, we observe no statistically significantdifference in the response of wages to international migration shocks.

Finally, the partition of the sample between high receivers of FDI (above themean) and low receivers (below the mean) suggest that the response of real wages todomestic and international migration is significant and differs for the twosubsamples but the difference is not substantial. We observe only a slightly higherresponse of real wages to foreign and domestic migration supply shocks across stateswith higher than average reception of FDI flows.

V. Concluding Remarks

Comparing wages of workers between 1990–2000, Chiquiar (2008) shows thatregions more exposed to globalisation exhibited an increase in overall wage levelsrelative to other regions in the country. This paper examines aggregate wages in


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Mexico for the period from 1997–2006, which is after the transition period followingthe floating of the peso to the US dollar in December 1994. At the same time, severalforces contributed to making Mexico more open to foreign capital in order tocomplement trade-related activities spurred by the NAFTA agreement. It is alsowell-known that international migration (legal and illegal) to the US has intensifiedover the period, likely to be a response to better returns for labour and workingconditions relative to the cost of moving.It is worth emphasising the importance of controlling for domestic and

international migration, a result that can only be achieved using state level data.To the best of our knowledge this is the first paper that addresses the effects ofdomestic migration alongside international migration and foreign capital flows.Most previous studies have addressed international migration or FDI separately.The view in this paper is, therefore, that the equilibrium wage rate (determined in

theory by the marginal product of labour) is simultaneously affected by labour demandand labour supply forces, captured by FDI inflows and (domestic and international)migration respectively. We investigate the role of FDI inflows into Mexico as capturingforces in the capital market, as well as migration movements within Mexico andbetween Mexico and the US to gauge the labour market dynamics. In contrast toRobertson (2005), who used border enforcement by the US border patrol whenmeasuring (illegal) international migration, we use recently available data fromMexico’s CONAPO that provides a new perspective on this issue.

Figure 5. Geographical location of domestic migration net flows across Mexican states.Source: Calculated using data from the National Population Council, Ministry of Employ-

ment (CONAPO).


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Our estimates provide some interesting results. First, we find strong and positiveeffects on real wages from foreign investment but, also, from international anddomestic migration. This is interesting as much attention has been given to the effect ofMexico’s international migration on real wages but little to the flows of domesticmigrants across states (Figure 5 indicates the magnitudes), especially of unskilledlabour moving from the south to the north. Overall, the result on FDI versus migrationeffects is suggestive of stronger labour demand shifts than labour supply, which is inline with strong complementarities between capital and labour in production. Second,alternative partitions indicate that real wages are more sensitive to FDI-relatedfluctuations across states with relatively lower wages and migration levels.

Our findings indicate very strong and positive effects on real wages from foreigninvestment and smaller effects from migration. Alternative partitions of our sampleshed additional light on these central results but the conclusion from this panel studyof 32 Mexican states is that factors from labour demand are likely to be the onesdriving wages in Mexico. Recently, the discussion in the Mexican press regardingforeign capital has dealt, for example, with the possibility of allowing foreign firms toparticipate in the much needed investment plans of state-owned PEMEX inexploring the national oil reserves. Our results are clearly supportive of the positiveeffects on Mexican real wages of foreign capital flows. The direct policy implicationof this study is that real wages will increase in Mexico with legislation that allowscapital inflows to come more freely into the country.

Notes

1. FDI and trade figures are taken from the International Monetary Fund database, International

Financial Statistics; migration rates are calculated with data from CONAPO, the Mexican

government national council of population.

2. For the years 1994–2005, Waldkirch (forthcoming) finds mixed results. On the one hand, total factor

productivity (TFP) appears to be positively affected by FDI, especially US FDI into non-maquiladora

sectors. On the other hand, the effect on average wages is negative or zero, depending on the

specification. This empirical mix casts doubt on the link between productivity and wages, which is not

directly treated in this paper.

3. This measure corresponds to the average wage received by permanent employees registered at the

Mexican Institute of Social Security (IMSS) in urban and rural areas. This measure is the same we

employ later at the state level to observe the effect of openness on wages.

4. Our approach uses these migration measures as regressors in the wage equation at the state level in

order to gauge labour supply shifts. Dahl (2002) develops a model of mobility and earnings where

workers choose in which of the 50 US states to live and work. His empirical work uses the 1990 US

census data and confirms the role of comparative advantage in mobility decisions. The relative state-

to-state migration flows of college versus high school educated individuals respond strongly to

differences in the return to education and amenities across states. Dahl’s (2002) approach is beyond

the scope of this paper.

5. For the construction of international and domestic migration flows and rates, CONAPO employs

census data from Censos Generales de Poblacion y Vivienda available every 10 years (year ending in 0)

and surveys made inbetween each census from Conteo de Poblacion y Vivienda (years ending in 5).

Projections for the years in between are calculated by CONAPO. Full details can be found at: http://

www.conapo.gob.mx/00cifras/00indicadores/documentacion_tecnica.pdf

6. With an average FDI/GDP share of 8.75 per cent, Distrito Federal (DF) has a larger FDI share in our

panel than other states. This figure is not, however, disproportional to the average and the shares of

other main receptor states of foreign capital such as Baja California, Baja California Sur, and Nuevo

Leon at 4 or 5 per cent of GDP. If the DF is the cross-section omitted from the estimations, the effect


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http://www.conapo.gob.mx/00cifras/00indicadores/documentacion_tecnica.pdf

http://www.conapo.gob.mx/00cifras/00indicadores/documentacion_tecnica.pdf

of FDI on real wages is likely to be smaller but not by much. Moreover, provided DF concentrates

more than 20 per cent of Mexico’s GDP, it is not surprising that it also receives the largest proportion

of FDI. Under the presence of measurement errors, Brulhart and Sbergami (2009) present further

advantages of the system GMM approach – used in this paper – compared to other estimators.

7. Geographically speaking, domestic and international migration patterns are also very different.

8. A similar derivation of the impact of an exogenous source such as FDI (which should affect the

absorption of technology) on labour demand can be found in Driffield et al. (2005). More recently,

Mollick and Cabral (forthcoming) have employed this set up to observe the effects of productivity on

labour demand of Mexican manufacturing.

9. Economic theory and Equation (2) suggest that wages are paid according to their contribution to

marginal product. In empirical work, marginal product is typically not available at the state level and

average product of labour serves as a proxy for the fundamental determinant of wages. In this

framework, output per capita is present in Equation (8). Output per capita also controls for the effect

of the economic crisis of 1995 and the influence of the recovery on wages: ‘the business cycle effect’.

10. As mentioned above, (domestic or international) migration rates are calculated as the difference

between outflows and inflows of people over total population.

11. Faria and Leon-Ledesma (2005) extend Lucas and Rapping’s (1969) intertemporal substitution labour

supply to an open economy and derive a labour supply that is a function of the real wage, real interest

rate and the real exchange rate.

12. Note that under static methods, lagged real wages are omitted from the estimates in Table 2. The

estimates are in principle not biased as a result of correlation between the errors and the explanatory

variables of the model.

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Appendix

The SGMM Approach

The growth equation for wages has the form:

wit � wit�1 ¼ awit�1 þ gXit þ mi þ ut þ eit ðA:1Þ

where: mi ut and eit are stochastic terms. (A.1) can be rewritten as:

wit ¼ a0wit�1 þ gXit þ mi þ ut þ eit ðA:2Þ

where a0 ¼ (aþ 1). In the panel data context, mi is a state-specific effect representingtime-invariant determinants of real wages that may or may not be correlated with(RHS) variables. Arellano and Bond (1991) propose a dynamic panel GMMestimator for (A.2), based on first-differencing the data, eliminating the panel effects


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in mi, and having as instruments all potentially endogenous variables (wit-1, Xit) withtheir own lagged levels. It has been shown by Blundell and Bond (1998), however,that the AB estimator behaves poorly in small samples when a’ ! 1 and when thevariance of mi is large compared to the variance of eit. It may be that when laggedlevels represent weak instruments for the first-difference variables, the AB estimatorsuffers from finite sample bias.The SGMM is shown by Blundell and Bond (1998) to yield considerable

improvements over the AB estimator in small samples. Bun and Windmeijer (2007)show that SGMM consistently has the smallest bias of all dynamic GMMestimators. It is based on a system composed of first-differences instrumented onlagged levels, and of levels instrumented on lagged first-differences. The orthogon-ality conditions between the control variables and mi, as well as between real wagesand mi must be satisfied, which is subject to empirical testing. The SGMM estimatorattempts to minimise simultaneity bias in order to isolate the causal effect that runsfrom the control variables to real wages. In addition to the simultaneity problem,Brulhart and Sbergami (2009) present further advantages of robustness tomeasurement errors.


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Documents

Capital and Labour Mobility and their Impacts on Mexico's Regional Labour Markets