metadata: authors: 0: author: Almeida,Rita Kullberg
count: Portugal
docna: 0: docna: The labor market effects of foreign-owned firms
docty: Policy Research Working Paper
subtopic: Construction Industry,Common Carriers Industry,Food & Beverage Industry,General Manufacturing,Pulp & Paper Industry,Plastics & Rubber Industry,Labor Markets,Educational Sciences,Business Cycles and Stabilization Policies,Transport Services,Rural Labor Markets
teratopic: Infrastructure Economics and Finance
abstracts: cdata!: Foreign firms often have a more educated
            workforce and pay higher wages than domestic firms. This
            does not necessarily imply that foreign ownership translates
            into higher demand for educated workers or higher wages,
            since foreign investment may be guided by unobservable firm
            characteristics correlated with the demand for educated
            workers or wages. The author examines foreign acquisitions
            of domestic firms in Portugal in the 1990s and finds small
            changes in the workforce skill composition and wages
            following acquisition. Foreign investors "cherry
            pick" domestic firms that are already very similar to
            the group of existing foreign firms.
geo_reg_key: 517208,517190,517191
repnme: repnme: The labor market effects of foreign-owned firms
display_title: The labor market effects of
            foreign-owned firms
listing_relative_url: /research/2004/05/4264194/labor-market-effects-foreign-owned-firms
topicv3: Labor Markets m1326488 855,Manufacturing Sectors m1326521 1281,Transport m1326661 135,Education m1327048 470,Labor Demand m1583073 4422
publishtoextweb_dt: 2010-07-01T00:00:00Z
historic_topic: Infrastructure Economics and Finance
no_of_pages: 33
author_keys: 0: author_key: 691150
model_extractions: WPS 3300

# The Labor Market Effects of Foreign-owned Firms<sup>∗</sup>

Rita Almeida DECRG The World Bank April 21, 2004

## Abstract

Foreign fi rms often have a more educated workforce and pay higher wages than domestic fi rms. This does not necessarily imply that foreign ownership translates into higher demand for educated workers or higher wages, since foreign investment may be guided by unobservable fi rm characteristics correlated with the demand for educated workers or wages. I examine foreign acquisitions of domestic fi rms and fi nd small changes in the workforce skill composition and wages following acquisition. Foreign investors “cherry pick” domestic fi rms that are already very similar to the group of existing foreign fi rms.

Keywords: foreign direct investment, acquisitions, employment, wage structure and panel data.

JEL Classi fi cation codes: C31, F23 and J31.

> ∗I am specially grateful to Antonio Ciccone for raising my interest in the topic and for his guidance and to Pedro Carneiro for several comments. I am also grateful to the Portuguese Ministry of Employment’s Department of Statistics for access to the data and, in particular, to Ermelinda Lopes and Artur Simões for their help. I also thank Bruno Cassiman, Mário Centeno, Koen Debacker, Jaume Garcia, Maia Güell, Sergi Jimenez, Adriana Kugler and José Mata for several suggestions. I bene fi ted from comments made by participants at the 7<sup>th</sup> meeting of the Portuguese Economic Society, Universitat Pompeu Fabra, XXVII Simposio de Analisis Economico(Salamanca), Universidade Nova de Lisboa, CEPR conference on “Globalization and labor markets”(Bergen) and at the DECRG, World Bank. I gratefully acknowledge the fi nancial support of Fundação para a Ciência e Tecnologia. The fi ndings expressed in this paper are those of the author and do not necessarily represent the views of the World Bank. Address: 1818 H Street, NW, MSN MC3-301, Washington, DC 20433, USA. E-mail: ralmeida@worldbank.org
# 1. Introduction

Regions and countries compete for foreign investment because it is perceived to have several bene fi ts for the host economy (Caves, 1996). For example, foreign fi rms often are associated with better technology, which may spill over to domestic fi rms<sup>1</sup> . Moreover, their jobs are perceived to be good in the sense that they require more quali fi cations, offer more training or pay higher wages. These reasons have been used to justify regional or national industrial policy in order to secure foreign investment.

Existing empirical work comparing foreign and domestic fi rms has shown that foreign fi rms have a more educated workforce and pay higher wages than domestic fi rms. But these fi ndings may at least in part be driven by selection of foreign investment into certain fi rms or sectors. For example, consider the fi nding that foreign ownership is associated with higher wages. This may be driven by wages increasing after the foreign acquisition, or by foreigners buying domestic fi rms that pay above-average wages. In this paper, I use panel data on Portuguese fi rms to provide evidence on the type of domestic fi rms bought by foreigners and on the effect of foreign acquisitions on skill composition and wages. I fi nd that foreigners “cherry pick” domestic fi rms, choosing those fi rms with an educated workforce and higher wages. Moreover, these fi rms are already very similar to the group of existing foreign fi rms. Following the foreign acquisition, I fi nd no signi fi cant changes in the educational composition of the workforce. There is evidence that average wages increase following the foreign acquisition but changes are smaller than cross-sectional estimates of this The positive wage premium for foreign fi rms is a stylized fact for developed and developing countries. Feliciano and Lipsey (1999), using industry-level data for the US for the period 1987-1992, fi nd a differential in favor of foreign fi rms that is larger for services (9-10 percent) than for manufacturing (5-7 percent). For UK manufacturing establishments, Girma et al. (1999) fi nd that foreign fi rms pay, on average, about 5 percent higher wages than domestic fi rms, even when sector, establishment size and productivity are controlled for. For Mexico

> 1For example, Dimelis and Louri (2001), Haskel et al.(2002) and Aitken et al.(1996) fi nd evidence consistent with positive spillovers to the host economy.

2
and Venezuela, Aitken et al. (1996), also fi nd higher wages for foreign fi rms. With competitive labor markets, there is no reason for a positive foreign wage premium unless workers or fi rms differ in some unobservable characteristics. In most of the fi rm level data sets used in the empirical literature, worker level information such as education, experience and tenure of the workforce is not collected. The assumption in this work is that omitting these characteristics does not generate signi fi cant biases in the estimation of the differences between domestic and foreign fi rms. Lipsey and Sjoholm (2003) control for the worker’s education and other worker level characteristics but they still fi nd a foreign wage premium in a cross section of Indonesian fi rms. Conyon et al. (2002) and Lipsey and Sjoholm (2002) try to overcome the problem of the unobservable fi rm characteristics that are correlated to the fi rm nationality by analyzing the impact on average wages of a foreign acquisition. Conyon et al. (2002) fi nd that average wages increase by 3.4 percent following a foreign acquisition but they do not control for any workforce characteristics. Lipsey and Sjoholm (2002) fi nd that average wages of blue and white collar workers increase by 10 percent and 21percent respectively. Both fi nd evidence that part of the cross section wage premium in manufacturing is due to a causal effect of foreign investment on wages. An alternative explanation for the foreign wage premium is based on imperfect labor markets. For example, if foreigners incur in higher search costs they may pay more to workers in order to discourage turnover. If foreign fi rms offer more training, have less power with unions or are more likely to adhere to minimum wages, they may also pay higher wages. Moreover, foreigners could pay higher wages simply because they have higher pro fi tability than domestic fi rms (rent sharing theories<sup>2</sup> ).

In this paper I analyze the Portuguese case which combines two important features. First, Portugal had a permissive legal framework for the operation of foreign fi rms that translated into generous amounts of foreign direct investment (FDI) in the late 1980s and 1990s<sup>3</sup> . Before becoming an European Union member in 1986, the amount of FDI in Portugal never 2Rent sharing theories argue that the labor market is not competitive as empirically wages are correlated with measures of the fi rm or industry “ability to pay”. See e.g. Blanch fl ower et al. (1996) for evidence on the US manufacturing.

> 3The importance of European Union and OECD as sources of FDI is clear: in 1992, 76% of the FDI came from the EU and 89% from OECD countries.

3
reached 1 percent of GDP (3.2 percent of total investment); in the early 1990s it tripled to 3.2 percent (12 percent of total investment in 1990). Second, a comprehensive fi rm level data set covering the 1990s is available. In particular, the fi rm and its foreign participation can be traced over time, making this data particularly suited for the analysis of FDI on labor demand and wages<sup>4</sup> .

One of the relevant topics in the policy debate is the impact of FDI on labor markets and, in particular, on employment and wages of the different educational groups. Mata and Portugal (2002) document that, in Portugal during the 1980s, foreign start-ups and foreign acquisitions<sup>5</sup> had a more educated labor force than domestic start-ups. They also fi nd that foreign start-ups and foreign acquisitions pay, on average, higher wages than domestic startups. However, one of the reasons for this fi nding might be the educational level of workers in the new foreign and domestic fi rms<sup>6</sup> . The most important difference between their work and my paper is that I am interested in identifying the effect of foreign acquisitions on labor demand and wages. Moreover, I am also interested in identifying how fi rms acquired by foreigners differ from the typical domestic fi rm.

Using data for the period 1991-1998, I start by analyzing differences in workforce educational composition and wage structure between foreign and domestic fi rms, without making any distinction between foreign acquisitions and existing foreign fi rms. A large part of the differences are explained by the sector and regional composition of foreign fi rms and, to a lower extent, by other fi rm and worker characteristics usually unaccounted for due to lack of data. But even after controlling for these characteristics, signi fi cant differences remain in wages and workforce characteristics of domestic and foreign fi rms. For example, in manufacturing, foreign fi rms have a proportion of low educated workers 7 percentage points lower than domestic fi rms and pay 15 percent higher wages, even after controlling for regional and

> 4Abowd et al. (1999) use a matched employer-employee data set for France, very similar to the data used in this paper. They fi nd that fi rm effects, while important, are not as important as unobservable individual effects in explaining wage variation.

> 5Foreigners may start operating in a country by two different ways: green fi eld entry (start-ups) or acquisition of an ongoing fi rm.

> 6 Machado and Mata (1998) using data for Portugal, between 1982 and 1994, found also that foreign fi rms pay higher wages and that this premium was larger for higher wages.

4
sector composition as well as size and age of the fi rm.

The data set I use allows me to identify the group of fi rms that switch from domestic to foreign ownership during the 1990s. Therefore, I make two contributions to the literature on the effects of foreign fi rms on the labor market. First, comparing outcomes before and after foreign acquisitions one can control for fi rm unobserved heterogeneity since it seems likely that some of the unobservable characteristics of the fi rm do not change over time and can be captured in a fi xed effect. Second, comparing the group of acquired fi rms with the typical domestic fi rm in the pre-acquisition period, I can assess the extent to which fi rms acquired by foreigners differ from the typical domestic fi rm.

One of my main fi ndings is that there exists an important selection effect as foreigners “cherry pick” domestic fi rms with a more educated workforce. For example, looking at manufacturing fi rms that were acquired by foreigners between 1993 and 1996, I fi nd that, two years before the acquisition, they have a proportion of low educated workers 9 percentage points lower than that of domestic fi rms in the same sector of activity and pay higher wages to all education groups (differentials range from 17 percent for the low educated to 39 percent to the high educated workers). In fact, domestic fi rms that were acquired between 1993 and 1996, already looked very similar to existing foreign fi rms in workforce composition and wage structure. I also fi nd that there are no signi fi cant changes in the fi rm’s workforce composition following a foreign acquisition. Wages increase for most of the education groups after the acquisition, even though this increase is smaller than in cross-sectional comparisons of domestic and foreign fi rms.

The plan of the paper is as follows. In the next section, I describe the data used and present some descriptive statistics. Section 3 explains the econometric methodology, presents and discusses the results on workforce composition. Section 4 and discusses the results on wage structure. Section 5 concludes.

5
# 2. Data

The data set used is a survey conducted every year by the Portuguese Ministry of Employment, “Quadros do Pessoal”. It is a longitudinal data fi le matching fi rms and workers. The data is based on a questionnaire that every fi rm with wage-earners operating in Portugal is legally obliged to fi ll out<sup>7</sup> . Records are available at the fi rm and plant level, and have a detailed description of the labor force characteristics<sup>8</sup> .

Among other fi rm characteristics, the share of equity owned by non-residents is reported. Therefore, for every fi rm I am able to identify whether the foreign investment is (1) an acquisition of an existing domestic fi rm, (2) a fully owned subsidiary or (3) a minority or majority holding. I use a 10 percent threshold of foreign participation to classify a fi rm as foreign and also to identify ownership changes<sup>9</sup> . Evidence in panel 5 of Table A1 in the Appendix shows that the choice of a 10 percent threshold is not too restrictive. In manufacturing, more than half of the foreign acquisitions have the full control of the fi rm, while foreign fi rms prefer majority stakes. In non-manufacturing, the foreign participation, in both foreign and acquired fi rms, is preferentially one of full control. At the worker level, I use information on the education level, sex, age, tenure and hours worked. This information is then aggregated, by education groups, at the fi rm level. The three education groups used are: low (up to 6 years of schooling), medium (high school and technical courses) and high (bachelor and college degrees). Gross monthly wages are computed summing up monthly earnings as well as other regular and irregular payments. Hourly wages are gross wages divided by total monthly hours worked (including overtime). Firm average wages are computed excluding the extreme values for hourly wages<sup>10</sup> . Throughout the paper I use

> 7Public Administration is not included.

> 8The survey has information for an average of 180,199 fi rms and of 2,248,076 employees per year, during 1991-1998.

> 9Ownership is related to those who make decisions about resources, but the relevant concept for policy purposes is that of control. Measuring control is difficult and, even if a fi rm acquires more than 50% of the shares of another, it may choose not to exercise its controlling rights. On the other hand, even without majority an owner may have the effective control (McGuckin, 2001, discusses this issue).

> 10Workers with implausibly low earnings (hourly wage lower than 50% of the minimum wage) or implausibly high earnings (irregular payments -like dismissal payments- exceeding twice the other monthly wage components) were excluded from the sample. There were few of these cases.

6
hourly real wages per employee to control for differences between foreign and domestic in the hours worked<sup>11</sup> . The consumer price index comes from National Department of Statistics. The level of aggregation used for region and sector composition was Nuts1-region<sup>12</sup> and three digits sector classi fi cation<sup>13</sup> .

The selection of fi rms that were acquired by foreigners is done according to the following criteria. First, I identi fi ed all the fi rms that have operated for two consecutive years with 100 percent domestic capital and that for the next three years have at least 10 percent of foreign capital. Therefore, while these fi rms are newly foreign, they existed before under domestic ownership. Second, I restrict the analysis to fi rms that operated for at least fi ve consecutive years. If the analysis is to be based on the change in ownership, it is important to have information on the fi rm two years before the acquisition in order to analyze the fi rm’s choices before the ownership change, while the use of the following two years ensure that the fi rm does not exit immediately after. Even though the sample period for identifying foreign acquisitions is 1993-1996, it stretches to 1991-1998, due to these requirements. Third, the sample is restricted to fi rms with more than 30 employees in every surveyed year. Fourth, the fi rm must be located in continental Portugal and cannot operate in the primary sector in any surveyed year<sup>14</sup> . The selection of fi rms that remain always under domestic and foreign ownership was as similar as possible to the sample of acquisitions. First, they must operate for at least fi ve consecutive years. Second, during that period a domestic fi rm can never be foreign participated and foreign fi rms have always at least 10 percent of foreign ownership.

> 11Workers of foreign owned fi rms work on avearge less hours than workers in domestic fi rms. E.g., low educated workers in foreign fi rms work 171 hours per month (173 hours in domestic fi rms) and high educated workers work 166 hours (168 hours in domestic fi rms).

> 12Eurostat divides the european countries into Nuts (Nomenclature of Territorial Units for Statistics). These can vary between Nut 1 to Nut 3, according to the disagregation level. The Nut 1 classi fi cation divides Portugal into 5 regions: North, Center, Lisbon Area, Alentejo and Algarve.

> 13Because the national sector classi fi cation changed in 1994, I assumed that, between 1991 and 1995, there is no change in sector classi fi cation at three digit level by using the fi rm sector classi fi cation in 1995.

> 14The usual problem of the non-random exit of acquisitions from the sample (attrition) does not seem to be severe in this data. Mata and Portugal (2002) fi nd evidence that the survival rates for acquired fi rms are very high. After fi ve years of operation more than two thirds and more than four fi fths of the foreign green fi eld and acquisition entrants are still in operation. This is not the case for the UK, where Girma and Görg (2001) fi nd that foreign acquisitions reduce the probability of survival of the plant in the electronics industry.

7
Third, they must have at least 30 employees in every sampled year. Fourth, they must be located in continental Portugal and cannot operate in the primary sector<sup>15</sup> . The fi nal sample is an unbalanced panel of 3,410 domestic fi rms, 194 foreign fi rms and 103 foreign acquisitions of domestic fi rms<sup>16</sup> . I have also identi fi ed a group of 37 domestic acquisitions of foreign fi rms (24 in manufacturing and 13 in non-manufacturing<sup>17</sup> ). Due to the small number of these observations I focus the analysis on the group of foreign acquisitions<sup>18</sup> .

Table A1 in the Appendix characterizes the fi nal sample in several dimensions. Panel 1.6 shows that sector composition of the foreign investment explains part of the wage differentials between foreign and domestic fi rms. The proportion of fi rms located in the top highest paid sectors are at least two times larger in foreign owned fi rms than in domestic fi rms. Therefore, a better measure of the differences in skill composition and wages between foreign and domestic fi rms must control for the fact that foreign fi rms tend to be concentrated in different sectors of activity. Let p<sup>k</sup> js<sup>be theshare ofeducation group kin thetotalworkforce</sup> of foreign fi rm j operating in sector s, p<sup>k</sup> s<sup>be the share of education group kof domesticfirms</sup> operating in sector s, wjs<sup>kbetheaveargehourlywageofeducationgroup kinforeignfirm j</sup> and ws<sup>ktheaveragehourlywageofeducationgroupkindomesticfirmsoperatinginsector</sup> s. Column (1) of Table 1 reports the average difference across all sectors for p<sup>k</sup> js<sup>−pk</sup> s<sup>and</sup> lnwjs<sup>k−lnw</sup> s<sup>k.The differences in employment are reported as the average across sectors of the</sup> empjs<sup>whereempjsistheemploymentoftheforeignfirmjoperatinginsectorsandemps</sup> emps<sup>,</sup> is the average employment in the domestic fi rms of the sector. I compute the differences between fi rms operating in the same two-digit sector of activity. Panel A reports the results for manufacturing sectors and panel B for non-manufacturing sectors.

Column (1) compares foreign and domestic fi rms. In manufacturing, the share of low ed-

> 15The primary sector includes agriculture and mining. Firms operating in 3 digit sectors with exclusively domestic fi rms that fi ll in these requirements were excluded from the sample.

> 1673% of the domestic fi rms in the sample and 58% of the foreign and acquired fi rms operate in manufacturing sectors. More than 90% of the fi rms in the sample are observed for more than six years. 1% of domestic fi rms are observed for less than fi ve years because they have less than 30 workers in the worker’s fi les during that year.

> 17There are only two fi rms that fi ll these requirements and that experienced more than one ownership change, i.e., a foreign and a domestic acquisition).

> 18However, at the end of each section I discuss the fi ndings when this sample is also included.

8
ucated workers is 9 percentage points lower than that of domestic fi rms, while the groups of medium and high educated workers have shares 7 percentage points and 3 percentage points, respectively, higher than those of domestic fi rms. In non-manufacturing, these differences are even greater with the share of low educated workers 25 percentage points below, and of medium and high educated workers 13 percentage points and 12 percentage points above that of domestic fi rms, respectively<sup>19</sup> . This evidence shows that foreign fi rms have a more educated workforce, both in manufacturing and non-manufacturing, and that these differences are quantitatively important. Also, foreign fi rms employ on average, 3.5 times and 2.2 times more employees than domestic fi rms in manufacturing and non-manufacturing, respectively. Given the differences in the educational composition, it is not surprising to fi nd differences in the average wages among domestic and foreign fi rms. In manufacturing foreign fi rms pay wages 26 percent higher than domestic fi rms and in non-manufacturing 55 percent higher. Wage differences within education categories are also substantial. Also, the foreign wage premium increases with education. This fi nding is important, since it shows that the wage differential cannot be entirely explained by differences in the educational workforce composition nor by sector composition of foreign fi rms, even though region and sector location are important in explaining the wage differentials<sup>20</sup> .

Columns (2) and (3) in Table 1 compare acquired fi rms with domestic fi rms two years before and one year after the foreign acquisition, respectively. For example, fi rms in manufacturing two years before becoming foreign owned have, on average, a share of low educated workers 8 percentage points below that of domestic fi rms in the same sector. This difference increases to 10 percentage points one year after the acquisition. Differences in nonmanufacturing are even larger with the share of low educated workers 21 percentage points below that of domestic fi rms in the same sector. The magnitude of the wage differences is also large and quantitatively very similar to the ones in column (1). This shows that acquired domestic fi rms were already very different from the average domestic fi rm in the same sector

> 19Table A2 in the Appendix shows that manufacturing has a less educated workforce and pays, on average, lower wages than non-manufacturing. These wage differences prevail within education groups.

> 20These are unweighted means.

9
of activity before the acquisition both in manufacturing and non-manufacturing. Therefore, acquired fi rms have a more educated workforce and pay higher wages than domestic fi rms to all the education groups<sup>21</sup> . The comparison of columns (2) and (3), shows the evolution following the foreign acquisition. Differences in the workforce educational composition increase both in manufacturing and in non-manufacturing. Also, acquired fi rms in manufacturing do not experience any change relative to the average wages of domestic fi rms, while in the non-manufacturing sector there is an increase in wages after the acquisition. Columns (4) and (5) present the comparisons between acquired and foreign fi rms two years before and one year after the foreign acquisition, respectively. Differences both in workforce composition and wages become much smaller and not statistically signi fi cant in manufacturing and non-manufacturing sectors<sup>22</sup> . Relative to foreign fi rms, acquired domestic fi rms are similar in size in manufacturing and are 50 percent larger in non-manufacturing.

Caves (1996) argues that foreign fi rms have a technological advantage over domestic fi rms, either generated by the ownership of some intangible assets (e.g. speci fi c technological knowledge, a brand name or superior organizational capabilities) or by a privileged access to external capital markets. If this is the case, we would expect this advantage of foreign over domestic fi rms to translate into a higher demand for skilled workers on the one hand, and into higher productivity, and therefore higher wages on the other. Descriptive statistics in this section show that foreign fi rms have a more educated workforce and pay higher average wages. The wage premium is in part explained by the higher human capital of foreign fi rms but that is not all, as differences are still prevalent within each education category. Furthermore, fi rms that will become acquired in the following two years already have a more educated workforce and pay higher wages than domestic fi rms in the same sector of activity. During this period, they already look very similar to foreign fi rms. But, as seen in Table A1, foreign fi rms tend to be located in the Lisbon area where average wage are higher, and

> 21The hypothesis that acquired fi rms have lower shares of low educated workers and higher shares of medium and high educated workers cannot be rejected in columns (1) to (3). The hypothesis of a positive wage differential for all the education groups is also not rejected.

> 22The hypothesis that acquired fi rms do not differ from foreign fi rms in the workforce composition and wages paid is not rejected in columns (4) and (5).

10
tend to be larger than domestic fi rms. Worker characteristics may also differ between foreign and domestic fi rms causing average wages to differ. I turn next to regression analysis where these and other rm and worker characteristics will be taken into account.

# 3. Employment in Foreign Firms

To analyze employment of skilled labor, I estimate the following model for the three education groups (low, medium and high): ykjt is fi rm j share of workers with education k at time t. forjt is a dummy variable if fi rm is foreign owned, therefore, at this stage I do not take into account if a domestic fi rm will become foreign owned latter on. Zjt is a vector of fi rm characteristics including both a set of dummy variables for the size of fi rm j at time t ( less than 49 workers, 50-99, 100-499, more than 500) and a set of dummy variables for the fi rm age (less than 5 years, 5-15, more than 15). Finally, αkt, αkr and αks are time, region and sector dummy variables, respectively. The year dummies control for economy wide shocks that affect one education group similarly across all fi rms. Differences due to regional location of the fi rms are captured by αkr and differences due to sector composition are captured by αks. Because the impact of the explanatory variables on the three education groups has to sum up to zero, these restrictions are imposed in the model<sup>23</sup> (e.g. βlow + βmed + βhig = 0). I estimate the three equations jointly as a system of seemingly unrelated equations. Table 2 presents the results for manufacturing<sup>24</sup> . Reported standard errors assume that disturbances are independently distributed across fi rms. Speci fi cation (1) reports the results of including only the variable forjt in the model. Foreign fi rms have a less educated workforce (proportion of low educated workers 15 percentage points lower than in domestic fi rms). Including explanatory variables as sector, region, size and cohort decreases the coefficients of low and medium ed-

> 23This procedure is standard in the literature estimating demand equations since the shares of expenditure in different goods must sum up to one.

> 24Throughout the paper I report the results separately for manufacturing and non-manufacturing sectors. I never accept that the models are the same for the two groups.

11
ucated workers in almost 50 percent: the share of medium and high educated workers are 5 percentage points and 2 percentage points above that in domestic fi rms, respectively<sup>25</sup> . Table 3 reports the same results for non-manufacturing. Again, part of the differences in the workforce composition between domestic and foreign fi rms are due to region, sector, size of the foreign fi rms. However, as reported in column (2) of these tables, even after controlling for these characteristics, the proportion of medium educated and high educated workers is 6 percentage points and 9 percentage points above that in domestic fi rms.

These cross-sectional fi ndings may at least in part be driven by selection of foreign investment into certain fi rms or sectors with a more skilled workforce. Table A3 in the Appendix shows that at the time of the acquisition, foreigners may choose among domestic fi rms operating in the same two-digit sector with very different workforce compositions<sup>26</sup> . By estimating the same model within two-digit sectors of activity I rule out the second hypothesis of sector selection. Table A4 in the Appendix shows that foreign fi rms have a more educated workforce within almost all two-digit sectors<sup>27</sup> .

# 3.1. The Sample of Foreign Acquisitions

One way to control for the unobservable characteristics that might explain the differences between foreign and domestic fi rms is by comparing the period before and after the acquisition for those fi rms that are acquired by foreigners. This sample, by construction, controls for part of the unobserved fi rm heterogeneity since it is the same fi rm changing ownership, and several things remain constant before and after the acquisition. For example, with information on acquisitions it is possible to know whether foreigners increase the demand for education or if they buy fi rms with the closest structure possible to theirs. To disentangle these effects, the following model is estimated for the sample of acquisitions and foreign

> 25To allow for differentiated impacts on the labor market outcomes according to the percentage of foreign capital, I estimate the same model with minority, majority and full foreign ownership dummies. Foreign fi rms have a more educated workforce for all groups and results are not statistically different between majority and full ownership.

> 26Table A3 in the Apendix computes the means and standard deviations for the proportions of high educated workers within each sector of activity for the domestic fi rms in the sample. The heterogeneity in the workforce composition also holds within a regions and sectors of activity.

> 27Sectors where the differences between foreign and domestic fi rms are highest include the wholesale and retail trade, transport and communication as well as real estate (all non-manufacturing sectors).

12
owned rms: where forjt is a dummy variable if fi rm j is foreign owned. The fi xed effect, ηkj, summarizes the impact of permanent differences in observed and unobserved characteristics affecting the outcome ykjt. The remaining variables have the same notation as above<sup>28</sup> . Finally, the error term, �kjt, is assumed to be uncorrelated across fi rms and time. The parameters in equation (3.2) are estimated, including the fi xed effects, by least squares. Thus, no matter how the fi rm’s permanent characteristics are related to the acquisition, the estimates of this effect are unbiased.

This estimation approach generalizes the differences in differences technique. The need for including another group of fi rms in the regression is made clear in Meyer (1994). Comparing an outcome before and after the acquisition is not sufficient because it could also be affected by other factors that are contemporaneous with the acquisition. Assuming that shocks contemporaneous to the acquisition affect acquired fi rms and control fi rms in the same way, the coefficient on the foreign ownership variable would be an unbiased estimator of the impact of ownership change. The main problem of applying this research design in this sample is that it is not appropriate when the two groups being compared are very different already during the pre-acquisition period. As suggested by the fi ndings in table 1, acquired and foreign fi rms are very similar with respect to their workforce composition. Therefore, to analyze changes in labor market outcomes following the foreign acquisition, I start by comparing acquired fi rms with other foreign-owned fi rms, as these are a better counterfactual than domestic fi rms. The important issue is to establish what would have happened to the fi rm had it not been acquired by foreigners. By using this group it is less likely that estimates are biased due to the selection.

Column (3) in tables 2 and 3 present the results of estimating equation (3.2) using foreign fi rms as control group. Following the acquisition, there are no signi fi cant changes

> 28Region and sector dummies are identi fi ed because there are switchers in these categories. However, empirical fi ndings do not depend upon their inclusion.

13
in the educational composition of the workforce in acquired domestic fi rms<sup>29</sup> . The only signi fi cant change is for the group of low educated workers in manufacturing, whose share falls by 1 percentage point following the acquisition. Table A5 in the Appendix shows that there is no evidence of signi fi cant changes following the acquisition in the size of the fi rms in manufacturing. Therefore, this decrease in the share of low educated workers is re fl ecting a decrease in the number of low educated workers. In non-manufacturing the number of employees increases by 25 percent and 27 percent, by the second and third year following the acquisition and, therefore, the number of low educated workers must increase accordingly<sup>30</sup> . To check the robustness of the results relative to the fi rms included in the control group, I estimate the same model including all the domestic and foreign fi rms in the sample. The results are presented in column (4) of table 2<sup>31</sup> . In sum, if foreigners choose to enter a market by acquiring an existent domestic fi rm, they may look for a fi rm where they need to make adjustments in the workforce composition or they may target a fi rm whose workforce composition is close to the desired level. My fi ndings show that foreigners choose this second option since there is no signi fi cant adjustment in workforce composition following the acquisition. This seems a reasonable strategy in the presence of important employment protection in the Portuguese labor market (see Blanchard and Portugal, 2001).

# 4. Wages in Foreign Firms

To analyze the differences in the wage structure for the three education groups, I estimate hourly wages per employee as a function of several fi rm and worker characteristics, including

> 29Although not reported, these results are robust to the inclusion of the domestic acquisitions of foreign fi rms in the sample.

> 30Speci fi cation (3.2) is restrictive as it estimates an average effect following the acquisition, and restricts the impact to be zero in the years before the acquisition. I allowed for a more fl exible speci fi cation where the acquisition can affect the workforce composition up to four years before and after the acquisition year (see Jacobson et al., 1993, for a similar methodology). For manufacturing I fi nd that, 3 years before the acquisition the proportion of low educated workers starts decresing and the proportions of medium and high increasing. Specially in the third year following the acquisition there is evidence of quantitatively important changes. In non-manufacturing, the share of low educated workers also has a negative trend that is accompanied by an increase in the share of the medium educated. These changes start three years before the acquisition and, again, are not statistically different from zero.

> 31For computational reasons the coefficients in this model were not restricted.

14
a foreign ownership variable: w stands for logarithm of real hourly wages per employee of education group k of fi rm j at time t. Xjtk is a vector of worker level characteristics within each education group k including the average age of the workers in the group, the average potential experience of the workers<sup>32</sup> , the average tenure on the fi rm and the proportion of females in the group. Squared terms for the age, experience and tenure variables were also included. The vector Zjt of fi rm characteristics includes size and age of the fi rm. The rationale for including the size of the fi rm on the wage equation is that foreign fi rms are, on average, larger, and some theories argue that larger fi rms pay more, either because efficiency wage theory is more effective when there is higher probability of long term relations, or because it is a compensating differential (a more dependable production process increases the cost of shirking). Finally, αkt controls for economy wide shocks that affect one education group similarly across all fi rms. Differences due to regional location are captured by αkr and differences due to sector composition are captured by αks.

Table 4 reports the results of estimating equation (4.1) by weighted least squares to control for heteroskedasticity since the data is aggregated by education groups within the fi rm. Without controlling for differences in other characteristics, foreign fi rms pay 28% higher wages for the low educated, 19% for the medium educated and 47% for the high educated in manufacturing. Controlling for sector, region, size and age of the fi rm (column (2)) accounts for almost 50 percent of these differences. However, the differences between foreign and domestic fi rms remain quantitatively important and statistically signi fi cant for all the education groups. Adding worker characteristics in column (3) does not imply substantial changes<sup>33</sup> . The foreign wage premium is higher for those workers with more than six years of

> 32Computed as age - years of schooling - six.

> 33I fi nd that for manufacturing sectors, larger and younger fi rms pay higher wages. Wages also increase with the average age of the workforce and the number of years of experience in the fi rm. Firm size, measured by total employment, is important for explaining wage differences in manufacturing (Feliciano and Lipsey, 1999). Large fi rms pay higher wages and because foreign fi rms are more than three times larger than domestic fi rms, the wage differential would have been 20 percent higher, not accounting for this characteristic.

15
schooling. The fi ndings for non-manufacturing in table 5 are somewhat similar. In column (1) foreigners pay wages 14% higher for low educated, 41% higher for the medium educated and 33% higher for the high educated. Controlling for fi rm characteristics implies a substantial decrease in the coefficients. Differences across fi rms in the characteristics of the medium educated account for part of the wage difference. However, after controlling for fi rm and worker characteristics I still fi nd a wage differential of 8% for the low educated, 16% for the medium educated and of 11% for the high educated<sup>34</sup> . In sum, the results suggest that controlling for observable fi rm and worker characteristics explains part of the wage differential but fails to explain fully the foreign wage premium. At least part of these differences can re fl ect differences in the wage premiums of foreign fi rms across sectors of activity. Evidence in Table A6 in the Appendix shows that even within 2-digit sector of activity the cross-section differences between foreign and domestic fi rms remain statistically signi fi cant in several sectors.

# 4.1. The Sample of Foreign Acquisitions

In this subsection I use the sample of foreign acquisitions to control for those fi rm unobservable characteristics correlated with higher wages and also with the foreign ownership. The model estimated is the following: where all the notation is as above.

The results of estimating equation (4.2), including the fi rm fi xed effects, by weighted least squares are presented in columns (4) and (5) of table 4 for manufacturing and in table 5 for non-manufacturing. In manufacturing, low, medium and high educated workers have increases in wages following the acquisition of 3%, 5% and 13%, respectively. These values are substantially smaller than the ones reported in the cross section. Therefore, part of the

> 34For non-manufacturing, wages are higher in fi rms with more than 100 workers and where the workforce has more experience in the fi rm. Contrary to manufacturing, worker characteristics like age and tenure on the fi rm are important in explaining wage differences. Controlling for the age of the fi rm has a small effect on the wage differentials of non-manufacturing (3 percent increase) and no effect in manufacturing.

16
cross section differences that we observe in the data are correlated with fi rm unobserved characteristics and, therefore, cannot be attributed to the foreign ownership itself. To test the robustness of the results, in column (5) I include all the domestic and foreign fi rms in the control group. I still fi nd that wage increases following the acquisition are substantially smaller than the cross sectional estimates. The fi ndings for non-manufacturing are reported in table 5. Wages for the low educated increase by 5% following the acquisition while the wages for the other groups remain unchanged. Including the domestic fi rms in the control group leads to an increase in wages of the medium educated by 4% while the wages of the high educated decrease in 4%.

The observed increase in average wages within education groups following an acquisition could be the result of a decrease in the number of low productivity workers in the fi rm or it could be the result of an increase in the average productivity per worker. The fi ndings in the previous section show that there is no substantial change in the educational composition of the workforce following a foreign acquisition. Assuming that fi rms are not replacing low ability workers by high ability workers within educational groups, my fi ndings are more supportive of the argument that average productivity increases following an acquisition. To test whether increases in wages are driven by increases in productivity I include as explanatory variable a proxy for the fi rm aggregate productivity. The best available measure in my data to measure productivity is the average sales per employee. This measure is likely to be plagged by measurement error, since it does not include intermediate goods. My assumption is that the fi rm fi xed effect atenuates this problem. The empirical results show that, although fi rms acquired by foreigners have increases in average sales per employee, the increase is uncorrelated with the foreign ownership in the wage equation<sup>35</sup> . In the presence of imperfect labor markets, foreigners might pay higher wages to workers with similar characteristics for several reasons. For example, if foreigners incur higher search costs they may pay more to workers in order to discourage turnover. If foreign fi rms offer more training, have less power with unions or are more likely to adhere to minimum wages,

> 35Results available upon request. The magnitude of the difference between foreign and domestic fi rms remains identical to the one reported in columns (4) and (5) of tables 4 and 5.

17
they may also pay higher wages.

Finally, I tested for the possibility that the increases in wages are the result of the acquisition itself rather than a result of the foreign acquisition by including in the sample the group of domestic acquisitions of foreign fi rms. If all the fi rms that are acquired have improvements in productivity and, therefore, higher wages, we would expect that including this group of fi rms would reduce the increases in wages following the foreign ownership. I fi nd that, after including these fi rms in the analysis, the wage differentials associated with foreign ownership are very similar to those reported in tables 4 and 5. Therefore, the results suggest that wage increases are not driven by acquisitions but by the foreign ownership itself<sup>36</sup> .

# 5. Conclusion

Cross sectional evidence shows that foreign fi rms have a more educated workforce and pay higher wages than domestic fi rms. These results do not necessarily imply that foreign direct investment translates into higher demand for educated workers or higher wages, however, since foreign investment may be guided by unobservable fi rm characteristics correlated with the demand for educated workers or wages. Using unique fi rm-level data for Portugal, I seek to isolate the effect of foreign direct investment on the demand for educated workers and wages by observing labor demand and wages of different education groups before and after the foreign acquisition. Existing empirical evidence for European countries is scarce and, apart from evidence for the United Kingdom, not much is known about the impact of foreign acquisitions on labor markets. Portugal is an interesting case, as in the late 1980s and 1990s there was a permissive legal framework for the operation of foreign fi rms that translated into generous amounts of FDI.

My three main fi ndings are the following. First, I show that foreign fi rms have a more educated workforce and pay higher wages for all education groups even after accounting for sector and regional composition, as well as other fi rm and worker level characteristics usually

> 36Unfortunatly, with this data I cannot identify the group of acquisitions of domestic fi rms made by national investors. If acquisitions lead to increases in wages, my estimates for the effect of foreign ownership on wages are over estimated.

18
not accounted for due to lack of data. Second, I fi nd evidence of an important selection effect as foreigners “cherry pick” domestic fi rms. Moreover, these fi rms are already very similar to the group of existing foreign fi rms and, following the foreign acquisition, there are no signi fi cant changes in the workforce educational composition. My third fi nding, related to the fi rst and second, is that heterogeneity at the fi rm level is very important for explaining differences in the labor market outcomes between foreign and domestic fi rms. In fact, there are no signi fi cant changes in the workforce composition following a foreign acquisition and, while wages increase for most of the education groups, these changes are smaller than the cross-sectional estimates.

19