Foreign Acquisition, Wages and Productivity

Roger Bandick
Aarhus School of Business, Denmark

Abstract
This paper studies the effect of foreign acquisition on wages and total factor productivity (TFP) in
the years following a takeover by using unique detailed firm-level data for Sweden for the period
1993-2002. The paper takes particular account of the potential endogeneity of the acquisition
decision (for example due to “cherry picking”) by implementing an instrumental variable approachand propensity score matching with difference-in-difference estimation technique. Moreover, in linewith recent literature on firm heterogeneity in international trade, this paper allows for theacquisition effect to differ depending on whether the targeted firms were domestic multinational or
non-multinationals before the foreign takeover. This paper also allows for the acquisition effect todiffer depending on whether the acquisition is horizontal or vertical. The result shows that foreignacquisition has no effects on overall, skilled or less-skilled wage growth neither in targeted Swedish
MNEs nor in targeted Swedish non-MNEs and neither if the acquisition was motivated by verticalor horizontal motives. However, the results indicate that both targeted Swedish MNEs and nonMNEs have better growth in TFP after vertical foreign acquisition only but no such impact fromhorizontal foreign acquisition.
JEL Classification: F23, L23, J31
Keywords: heterogeneity, multinational enterprises, acquisitions, wage differentials, productivity,
matching, difference-in-difference.

This draft, 24 August 2009

1.

Introduction

In the last two decades, international mergers and acquisitions (M&A) have increased substantiallyworldwide and, as a result, the share of foreign ownership in the total population of firms has grownin many countries. This has partly emerged due to different incentive programs by the hostcountries to attract foreign direct investment (FDI).1 From the point of view of the host country, theinward FDI may bring new technology and market access opportunities and thus strengthen theoverall competitiveness in the economy. However, the growing importance of M&As has given rise
to policy concerns due to the potential downside of foreign acquisition. It is frequently argued that
foreign takeovers may have a detrimental effect on the targeted firms’ performance since foreign
multinationals (MNEs) are less rooted in the local economy and have the possibilities of relocatingproduction among their affiliates in different countries.
In the light of the growing trends in international M&As, there are some important policy
implications for governments worldwide to investigate the effects of foreign ownership on takeover
targets performance. The objective of this paper is to study the effect of foreign acquisition on thetarget’s performance in the years following a takeover. I use recent unique detailed firm-level data
for Sweden to investigate the role of foreign ownership for wages and productivity growth intargeted firms.
Sweden is an interesting case to analyze in this context. Swedish authorities have implemented anumber of political reforms to improve the business environment and, as a result, Sweden is one of
the most internationally integrated and globalized economies in the world. However, it was not until
1995 in connection with the Swedish membership of the European Union (EU), that there was asubstantial increase in foreign ownership2. Ever since then, Sweden has witnessed a rapid increaseof inward FDI, mainly through mergers and acquisitions. Well-known former Swedish owned
firms, such as Astra, Pharmacia, Volvo Car and Saab Automobile, changed ownerships in the 1990s
and are nowadays foreign-owned. At the beginning of the 2000s, the employment share in foreignowned firms in manufacturing was among the highest in OECD.3

1

Golub (2003).
Malmberg and Sölvell (1998) stress that due to the Swedish membership of the EU, it has become more attractive toacquire Swedish firms.
3
As compared to 21 other OECD countries in 2002, only Ireland, Luxembourg and Hungary had larger employment
shares than Sweden in foreign- wned firms in manufacturing (Hansson et al. 2007).
2

1

The increase in foreign ownership has given rise to mixed feelings in the Swedish public debate,similar to other countries experiencing high growth of inward FDI. Some fear that foreignacquisitions will lead to job losses in acquired firms since foreign owners are less committed to thehost economy. It is frequently argued that, owing to their possibilities of relocating production andemployment among their affiliates in different countries, multinationals are more “footloose” thandomestic firms (e.g., Bernard and Sjöholm, 2003) and hence more quickly respond to adverse
shocks than domestic firms. However, foreign acquisitions can strengthen the competitiveness of
the acquired firms if they transfer technology, knowledge and skills to the acquired firms and,hence, contribute to an improvement in the target’s performance, e.g. higher productivity andwages.
From the theory on multinational enterprises (MNEs)4, there are strong suggestions thatmultinationals are more productive than other firms and also might pay higher wages than the
predominant wage level. The reason is that MNEs are supposed to possess firm-specific assets −unique products and production processes or intangibles, such as trademarks or reputations for
quality − that induce productivity and profitability gaps between MNEs and other firms. This idea
builds upon the conjecture that doing business abroad entails higher costs and risks than operatingon the domestic market; only the most productive and innovative firms will find it profitable toengage in foreign production.5 In addition, due to the firm-specific assets, MNEs have an
opportunity to pay non-competitive wages, i.e. in MNEs there exist some rents to be shared. The
efficiency wage literature then offers some economic reasons why such a behavior could be
profitable and increase productivity: (i) minimization of turnover costs6 (ii) motivation on workers’
efforts, (iii) enhancement of workers’ loyalty, and (iv) selection of workers with high quality.7
By now there exists a large body of studies analyzing the relationship between foreign ownershipand wages and productivity using panel data and the results are mixed. Conyon et al. (2002)
examine wage and productivity effects of foreign acquisition using company-level panel data for4

See the early contributions by e.g. Hymer (1960) and Dunning (1977). More recently, theories have been formalized
and Markusen (2002) provides a thorough and synthesized survey of the modern models on MNEs.
5
According to Dunning (1977), Markusen, (2002) and Helpman et al. (2004), only firms with a high productivity
choose to serve a foreign market and among these only the most productive will choose to establish affiliates abroad.
Helpman et al. (2004) also provide evidence that MNEs have significant productivity advantages relative to non-MNEs.
6
It could be imagined that MNEs are particularly concerned about worker turnover when their firm-specific assets
consist of proprietary technologies. Therefore, they may be willing to pay a wage premium to reduce the speed at whichthese technologies leak out to competitors as employees change jobs.
7
Stiglitz (1987) surveys the theoretical literature on efficiency wages.

2

UK manufacturing for the period 1988-1994. They find that wages and productivity increase after aforeign takeover of a domestic firm, controlling for firm size and fixed-firm and industry-specificeffects.
Girma and Görg (2007) investigate the wage effect of foreign acquisitions using panel data of
establishments in the UK food and electronics industries for the period 1981-1994. They apply
difference-in-difference (DiD) propensity-score matching methods and find sizable, positive postacquisition wage effects on skilled and unskilled labor following acquisitions by US firms, but nosuch impact from acquisitions by EU firms. By using the same data and estimation methods, Girma& Görg (2006) find positive productivity effects in foreign-acquired establishments only in theelectronic industries.
Huttunen (2007) investigates the wage effect of foreign acquisitions using panel data on Finnish
manufacturing establishments in the period 1988-2001, and her results indicate that foreignacquisitions have positive effects on wages. Martins (2004) and Heyman et al. (2007) are panel
analyses of individual wages and both studies use DiD propensity-score matching methods.
Heyman et al. (2007) find that the wage level is higher in firms targeted by foreigners than in nonacquired firms in the entire Swedish private setor. However, the wage growth in acquired firms islower than in firms that do not become foreign-owned. Moreover, Martins (2004) shows wage
growth to be lower in firms acquired by foreigners.
Bertrand and Zitouna (2005) and Ilmakunnas and Maliranta (2004) analyze the productivity effectof foreign takeovers in the manufacturing sector in France and Finland, respectively. Both studies
find that M&As significantly improve productivity in the targeted firms. Salis (2008), however,finds no effect on productivity as a result of foreign acquisition in Slovenian manufacturing firms.
Modén (1998) and Karpaty (2007) use a sample of Swedish manufacturing firms to analyze theproductivity effect in targeted firms. Modén (1998) finds mixed results while Karpaty (2007) finds
a positive difference in productivity between acquired and non-acquired firms.
I extend and improve upon these earlier papers in a number of ways. First, I focus on acquisition byforeign multinationals and use different econometric approaches to identify the causal effect of
takeovers in post-acquisition periods. To this end, I first estimate a DiD regression model taking
account of the potential endogeneity of the acquisition decision (for example due to “cherry
picking”) by implementing an instrumental variable approach. As an alternative estimation strategy,3

I use an extended version of the matched DiD method suggested by e.g. Blundell and Costas Dias
(2000) by in the first step matching, on a yearly basis, the non-acquired and acquired firms withsimilar propensity score and in the next step estimate DiD on the matched sample8 Second, using
the detailed and unique data for Sweden I am not only able to distinguish the differences in wages
and productivity between foreign MNEs and local firms, but also to separate domestically owned
firms into MNEs and non-MNEs. This is crucial since theoretical heterogeneous firm models ininternational trade (e.g. Helpman, 2006) predict that the decisive difference should be between
MNEs and non-MNEs, i.e. between foreign and domestic MNEs on the one hand, and non-MNEs
on the other. I therefore analyze whether the impact of foreign acquisition on wages andproductivity differs between takeovers of Swedish MNEs and non-MNEs. Third, I also allow theforeign acquisition effect to differ depending on whether the acquisition is horizontal (i.e within thesame industry) or vertical. To my knowledge, this has not been investigated in earlier studies.
To preview my results; I find, after controlling for possible endogeneity of the acquisition dummy
and also controlling for a large number of firm specific characteristics, that foreign acquisition has
no effect on overall, skilled or less-skilled wage growth in the post acquisition periods neither
whether the acquisition is horizontal or vertical or whether the acquired firms were domestic MNEs
or non-MNEs before the acquisition. However, I find positive productivity effect from verticalacquisition in targeted Swedish MNEs and non-MNEs, while I do not find evidence for an
acquisition effect from horizontal takeovers.
The plan of the paper is as follows. Section 2 presents the data and it shows some descriptive
statistics on foreign-owned firms, Swedish MNEs and non-MNEs to see to what extent they differ.
It also illustrates the increased importance of foreign ownership in Swedish manufacturing in the
1990s. Section 3 outlines the analytical framework and the econometric specifications. Section 4reports the empirical findings. Section 5 summarizes and concludes.

8This methodology allows for different vectors of covariates xt in the matching and in DiD estimations.

42.

Data and description

The dataset I employ in this study is from Statistics Sweden (SCB) and the Swedish Institute for
Growth Policy Studies (ITPS). The dataset includes information from financial accounts ofenterprises and register-based labor statistics for all manufacturing firms with 20 employees andmore and for the period 1993 to 2002. For each firm, I have information on sales, laborproductivity, capital-labor ratio, employment (skilled and less-skilled)9 and various production
inputs such as energy and intermediate costs. Moreover, I have information on firms’ ownershipstatus (foreign or domestic) and whether a domestic firm is MNE or not. A foreign-owned firm isdefined as a firm where foreign investors possess more than 50 percent of the voting rights and a
Swedish MNE is a domestically owned firm that is part of an enterprise group with at least one
affiliate and one employee abroad.10,11 Using this information, I can separate the firms into foreign
MNEs, domestic MNEs and domestic non-MNEs.12 Moreover, by using the information onownership status I can define foreign acquisition of a domestic MNE as a change in ownershipindicator from a domestic MNE to foreign and foreign acquisition of a domestic non-MNE as achange in ownership indicator from a domestic non-MNE to foreign.13
The clear distinction into different ownership status before the foreign takeover is a distinct
advantage of my data over the previous literature. This is an important dimension to the analysis
since the acquisition effect on firm performance, i.e. on wages and productivity, may differ whether
the target firms are multinational or not due to their ex-ante different characteristics as highlighted
by, for example Helpman et al. (2004). Due to data limitation, not many studies that haveinvestigated foreign acquisition have been able to take this into account.

9

Skilled labor is defined as employees with some post-secondary education.
This is the definition used in the official statistics on international enterprises from the Swedish Institute for Growth
Policy Studies (ITPS) and I can identify Swedish MNEs by linking data from ITPS to the microeconomic data from
Statistics Sweden (SCB).
11
My definition of Swedish MNEs differs from, for example, Heyman et al. (2007). In their study, Swedish MNEs are
firms that report positive exports to other firms within the corporation. Such a measure is obviously deficient sincefirms might be MNEs even though they are not exporting to their affiliates abroad.
12
1993 is the first year I can distinguish Swedish MNEs from non-MNEs and it explains why this analyze begins in1993.
13
Firms that switch between domestic and foreign ownership more than once over the period are not included in thesample. Also, firms that disappear from the sample one year and reappear in later years are excluded.
105

Another issue that has not been investigated in the previous literature, mainly due to data
availability, concerns the nature of the foreign acquisition and whether it is motivated by either
horizontal (the acquired firms are within the same industry as the acquirer) or vertical motives. The
effects of foreign acquisition on targets may be different depending on these two motives. If, forexample, the aim of the horizontal acquisition is to eliminate competition and consolidate theindustry, then it is likely that this may have a detrimental effect on the targeted firms’ performance
following takeover. On the other hand, if the aim of the horizontal acquisition is to create newmarkets by using the already exiting facilities owned by other firm in the foreign markets, i.e., theacquirer indents to “grow by acquisition”, then the acquirer may transfer technology and knowledge
in order to improve the quality in the acquisition target. In this case, we would expect positiveeffect on the targets performance in the post-acquisition period. For the acquisition motivated byvertical motives, this is more likely to be the case since the motive of the acquisition is to acquire
firms at different stages of the production process. It is then likely that the acquisition is done with aview to integrate the acquired firms into the multinational company structure which may lead totransfer of technology to improve or sustain quality.
In separating the foreign direct investment into horizontal and vertical I use the Swedish data andcheck the industry classification for the acquired firm before and after acquisition. If the two digit
industry code remains constant, I define the acquisition as horizontal and if it changed, I define theacquisition as vertical. Using this definition I classify about 19 percent of all foreign acquisitions in
my sample as vertical or non-horizontal.14
In the 1990s, many countries abolished or reduced their restrictions for foreigners to buy
indigenous firms and as a result FDI increased substantially worldwide.15 During this period,
Sweden also introduced a considerable amount of liberalization reforms and as a result, theincrease in foreign ownership seems to have been more pronounced in Sweden than in otherOECD countries.16 Table 1 shows how the numbers of firms and the employment shares have
14This is not an ideal measure by any means. In particular, it is likely that the vertical group includes both “true”
vertical acquisitions of, say, supplier firms, but also conglomerate mergers where the target and acquirer are in
unrelated industries. Unfortunately, I do not have sufficient information to establish industry linkages. Still, themeasure allows me to compare horizontal and other types of acquisitions.
15
Golub (2003).
16
See Hansson et al. (2007). Other explanations put forward for the increased foreign ownership in Sweden in the
1990s are that there were more invitations to acquire Swedish firms after the EU accession, Swedish firms were cheap
to buy due to the devaluation at the beginning of the 1990s and the Swedish tax system has favored foreign ownership.

6

developed among foreign MNEs, Swedish MNEs, and Swedish non-MNEs over the period 19932002. The employment share in foreign MNEs increased by almost 23 percent and their share of
the firms increased by 6 percent. This trend seems to have evolved at the expense of Swedish
MNEs since their employment share dropped by 19 percent and their share of firms has
decreased by 5 percent. The employment and firm share for Swedish non-MNEs remained fairly
constant over the period, however.

Table 1 here
During the 1990s, several large Swedish multinationals have become foreign-owned due toacquisitions by foreign MNEs, e.g. Pharmacia and Upjohn 1995, Saab Automobile and General
Motors 1998, Astra and Zeneca 1999 and Ford and Volvo Car Corporation 1999. Table 2 reports,
by year, the frequencies of foreign acquisitions in the manufacturing sector for firms with at least 20
employees. The number of foreign acquisitions varies considerably between years, from 29 in 1998
to 95 in 2001. In total, there are 464 foreign acquisitions and most of them, around 76 percent,consist of non-MNEs acquired by a foreign MNE.

Table 2 here
Firms taken over by foreigners differ from non-target firms in many respects. Table 3 points out
differences in characteristics and performance between acquired and non-acquired firms before andafter acquisition for all manufacturing firms with 20 employees or more. In columns (i), which
describe the situation one year before the acquisition ( T = −1 ), we can see that Swedish firms takenover by foreigners are larger, have higher sales, are more productive, are skill-intensive and havehigher wages than their non-acquired counterparts. Furthermore, acquired firms seem to have ahigher capital-labor ratio one year before the acquisition as compared to non-acquired firms. These
results provide us with some evidence of “cherry-picking”, i.e. that firms with good characteristics
and performance are more likely to be targeted for acquisitions by foreigners. From the othercolumns in Table 3 which depict the pattern at the time of acquisition ( T = 0 ) and after acquisition( T > 0 ), I infer that the differences between acquired and non-acquired firms appears to bepersistent.
Table 3 here7

Differences in characteristics and performance between acquired and non-acquired firms in theyears before acquisition could bias the estimates of the causal effect of foreign acquisition. To
overcome this problem, I use various methods: first, I estimate a regression model controlling for alarge number of observable firm characteristics. Second, I estimate a growth rate regression with
the implementation of instrumental variable approach using the predicted probability of being
acquired as an instrument (see McGuckin and Nguyen, 2001). Third, as a robustness check, I use
an extended version of the matched difference-in-difference (DiD) method suggested by e.g.
Blundell and Costas Dias (2000).

3.

The methodological framework

To come to grips with the direction of causality between foreign acquisition and wages and totalfactor productivity (TFP)17, I first estimate the following growth rate regression:

Δ ln y jT = ln y jt + s − ln y jt −1 = β 0 + β1 ln y jt + β 2 Acq jt + λ1ΔFirm jT+ γ 1 Industry + γ 2YearT + ε jTs ∈ {3,5}(1)

where Δ ln y jT is growth in average wage (w) or TFP in firm j between time period t − 1 and t + s ;s ∈ {3,5} . In some specifications, I divide average wage into skilled labor wage, ( w sjt ), and lessskilled labor wage ( w ujt ). Acq jt is a dummy variable that takes the value of one if firm j is foreignacquired at time t. ΔFirm jt is a vector of growth rate of firm-specific characteristics, such as
capital-labor ratio Δ ln ( K / L ) , shares of medium-skilled Δ ( MS / L ) and high-skilled labor
Δ ( HS / L ) , share of female workers Δ ( Female / L ) and size Δ ln ( employment ) .18 Industry jt is

17

TFP is calculated via the Levinsohn-Petrin (2003) method. I have also used TFP that is calculated by means of a nonparametric Divisia Törnqvist approach (see Karpaty, 2007) and value added per employee as different productivity
measure. The results, not reported in this study but can be sent upon request, do not qualitatively change using different
measure of productivity.
18
Employees with some post-secondary education are defined as skilled labor. Most likely, such a division into skilled
and less-skilled labor is more appropriate than the one which is often used, e.g. in Doms and Jensen (1998), i.e. the nonproduction/production worker classification. In addition, I divide skilled labor into medium-skilled and high-skilledlabor. Employees with a post-secondary education of three years or more are high-skilled labor and employees with apost-secondary education of less than three years are medium-skilled labor.

8

industry dummy variables19, Yeart is time dummies, and ε jt is an error term. The control groups ineq. (1) are firms that have not been acquired by foreign MNEs. β 2 then capture the differences inwages and productivity between acquired and non-acquired firms.
The acquisition dummy in equation (1) rests on the assumption that domestic firms taken over byforeign MNEs are randomly acquired. This assumption, as illustrated in Table 3, is a strong
assumption. If foreign acquirers choose targets with a priori positive characteristics, a practiceknown as “cherry picking”, then the estimate of the casual effect of foreign acquisition will bebiased. In order to control for the possible endogeneity of the acquisition dummy, I construct an
instrumental variable as the probability of a firm being taken over by a foreign MNE. This
instrumental variable is constructed as the predicted value of the dependent variable from a probit
regression for the probability of a foreign takeover, similar to McGuckin and Nguyen (2001) andConyon et al. (2002). The set of instruments, and the probit regression results, are reported in the
Appendix.
As an alternative estimation strategy to control for the possible selection bias and to examine
whether foreign-acquired firms enjoy a higher wage and productivity growth than non-acquired
firms, I use a Difference-in-Difference (DiD) estimation technique on a selected sample that is
generated using propensity score matching approach.20
The DiD estimator compares the difference in wages/productivity of the acquired (treated) firms A
in the period before (t-1) and in the period after (t+s) acquisition with our control group of non-

(

) (

)

acquired firms C. Formally, the parameter I want to estimate is λt + s = y tA+ s − y tA−1 − y tC+ s − y tC−1 andit can be obtained by regressing data pooled across the treated firms and the firms in the control
group:21

y jt −1,t + s = β 0 + β1 Acq j + β 2 Aftert + s + β 3 Acq j × Aftert + s + ε

19

s≥0

(2)

Industries are defined at the SNI92 3-digit level (99 industries).
The method is frequently used in the evaluation literature on active labor market programs. Heckman et al. (1999)
give a comprehensive overview of the labor economics literature. Becker and Ichino (2002) constitute a useful guide forhandling matching with Stata.
21
See Woolridge (2002).
20

9

where y jt −1,t + s is my outcome variable (wages or TFP) in period t − 1 to t + s . Acq j is again adummy variable taking the value of 1 for acquired (treated) firms, A, and 0 otherwise for nonacquired firms, C. It controls for constant differences in wages/productivity between target firms
and firms in the control group before the acquisition. I define the dummy variable Aftert + s as taking
the value of 1 in post-acquisition years t + s and 0 before acquisition t − 1 . This dummy variable
captures aggregate period effects that are common between the two groups A and C. Finally, theterm Acq j × Aftert + s is an interaction term between Acq j and Aftert + s . Its coefficient β 3 represents
the difference-in-difference (DiD) estimator of the effect of acquisition on the acquired (treated)firms A, i.e. β 3 = y t + s . An advantage of the DiD estimator is that it eliminates unobserved timeinvariant differences in wages/productivity between acquired and non-acquired firms. Table 4summarizes the interpretation of the coefficients in the regression in equation (2).

Table 4 here

The DiD is, however, not a valid estimator if the differences between acquired and non-acquired
firms are very high in the years before the acquisition. To get a more accurate estimator, I use asample where acquired firms (treated units) are matched together with similar firms that continue tobe domestically owned (non-treated units). Here, the matched non-acquired firms approximate forthe non-observed counterfactual event, i.e. what would on average have happened to the wages andproductivity in acquired firms had they not been acquired by a foreign-owned firm.
The matched sample is constructed as pairing, on a yearly basis, acquired with non-acquired firms
with similar pre-acquisition characteristics X, e.g. skill intensity, age, size etc.22 The method I adapt
is a propensity score matching due to Rosenbaum and Rubin (1983). This technique has theadvantage of summarizing all observables X into a single index variable. To implement a propensity
score matching, I begin by estimating the probability (or propensity score) of being acquired by aforeign firm using the same probit model as in the instrumental variable approach.

22This description of the essentials in matching techniques draws heavily on Bandick and Karpaty (2008).

10

Once the propensity scores are calculated, I can (by using the “calliper” matching method) selectthe nearest control firms in which the propensity score falls within a pre-specified radius as a match
for an acquired firm.23 Moreover, I check whether the balancing condition is verified, that is eachindependent variable does not differ significantly between acquired and non-acquired firms.
Another condition that must be fulfilled in the matching procedure is the so-called common supportcondition. This criterion implies that at each point in time, a newly acquired firm is matched with
non-acquired firms with propensity scores only slightly larger or smaller than the target firm.24
Furthermore, since my purpose is to study post-acquisition dynamics in wages and productivity, I
only include firms that remain at least five years in the panel.25
Since the aim of the matching is to find a group of acquired and non-acquired firms with similar
characteristics, I once more report, in Table A2, mean variable differences between the groups offirms that were successfully matched. Regarding to factor intensities and to firm size in terms of
employment and sales, the matching procedure has been successful in reducing the difference
between acquired and non-acquired firms. However, there are still significant differences in wages
and total factor productivity. Hence, in the estimation of the DiD I control for a vector of firm
characteristics to control for differences in observable attributes between firms. Moreover, to takethe remaining differences into account I estimate equation (2) with a firm-fixed effect (FE) model.

4.

Empirical results

4.1

The result of the growth rate model

The results based on the alternative way of generating the instrument for the acquisition
dummies, Acq jt , in equation (1) are reported in Table 5, models (1) to (3). In all estimates, I control

23

The procedure I utilize to match treated (acquired) firms with control (non-acquired) firms is the PSMATCH2 routine
in Stata version 9 described in Leuven and Sianesi (2003). In the analysis, the pre-specified radius is set to 0.01.
24Note that some acquired firms may be matched with more than one non-acquired firm, while acquired firms notmatched with a non-acquired firm are excluded.
25
Moreover, firms that switch back and forth between different ownership status and greenfield operations are
excluded.

11

for changes in firm-specific characteristics similar to those included in equation (1).26 To get arough indicator of whether or not the assumption of exogeneity holds, I use a standard Hausman
test. These tests, not reported in the table but available upon request, provide evidence that in allcases we can reject the assumption of exogeneity of the acquisition dummy.
In the first estimation, the results of estimating equation (1) for the period t − 1 and t + 3 arereported. In the first three columns the dependent variable is growth in overall wage. In columns(iv) to (vi) the dependent variable is growth in skilled wage and in columns (vii) to (ix) the
dependent variable is growth in less-skilled wage. Model (1) uses the instrument generated from theprobit regression described in the Appendix, Table A1, column (i). The result indicates that three
years after the acquisition, the wage growth, especially for skilled labor increased more in acquired
firms than in non-acquired firms. On average, the growth in overall wage, column (i), is 0.8 percent
higher in acquired firms after the takeover relative to non-acquired firms and the corresponding
figure for skilled wage growth, column (iv), is 1.9 percent. However, for the less-skilled wage
growth, column (vii), there seems to be no impact of foreign acquisitions three years after theacquisition.
In models (2) and (3), the findings are based on alternative definitions of the instrumental variable.
Model (2) uses the instrument generated in Table A1, column (ii), and the result for the overall,
skilled and less-skilled wage growth are similar to those reported in model (1). In model (3),however, which uses the instrument generated in Table A1, column (iii), there seems to be no
impact of foreign acquisitions on the wage growth.
In the last three columns of Table 5 I report the result from estimating equation (1) having growth in
TFP as dependent variable. The estimations in all three models are positive and highly significant
which suggest that foreign acquisition have had a positive effect on total factor productivity in theyears following acquisition. Depending on the alternative IV models, the difference in productivity
growth between acquired and non-acquired firms is between 3 and 9 percent three years after theacquisition.

26

Note that, in order to get accurate standard errors for the estimators using generated IV I compute bootstrapped
standard errors.

12

In the next estimation I examine the growth rate for the period t − 1 and t + 5 . From theseestimations I infer that up to five year after the acquisition, acquired and non-acquired firms have
had same development in overall, skilled and less-skilled wages. As to the result for the
productivity growth, it seems that foreign acquisition has lead to increase the productivity byroughly 2 to 4 percent for the acquired firms five years after the acquisition.
To allow for different impacts of foreign acquisitions on wages/productivity depending on whether
a Swedish MNE or Swedish non-MNE is acquired, I add in equation (1) interaction variables,

SMNE × Acq j and NonMNE × Acq j . The first interaction variable captures the DiD between
acquired Swedish MNEs and non-acquired firms while the second interaction variable captures the
DiD between acquired non-MNEs and non-acquired firms. Also to allow the acquisition effect todiffer for horizontal and vertical acquisition in equation (1), I add an interaction variable between adummy for horizontal acquisitions and the foreign acquisition dummies and similar for verticalacquisitions.
The results of estimating equation (1) with these modifications are reported in Table 5, estimation(3) and (4). Again the results are based on alternative IV models. I use similar probit models as in
the basic model of equation (1) to generate the IV for the dummies vertical acquired Swedish

MNEs, vertical acquired Swedish non-MNEs, horizontal acquired Swedish MNEs and horizontal
acquired Swedish non-MNEs. Estimation (3) reports the result for the period t − 1 and t + 3 andestimation (4) reports the result for the period t − 1 and t + 5 . From these two estimations I find no
impact from foreign acquisition on the wage growth neither in targeted Swedish MNEs or nonMNEs and neither if the acquisition was motivated by vertical or horizontal motives. The results,
however, indicate that both targeted Swedish MNEs and non-MNEs have better growth in TFP after
vertical foreign acquisition only but no such impact from horizontal foreign acquisition. Based on
the first IV model in column (x), a vertical foreign acquisition leads to an improvement in TFP
growth by 3.5 percent for targeted Swedish MNEs after three years and 2.7 percent after five years.
The corresponding figures for targeted Swedish non-MNEs are 3.1 percent after three years and 1.1
percent after five years.

Table 5 here

13

4.2

Difference-in-difference matching results

For a further robustness check, I first implement a propensity score matching procedure to generatea sample of acquired and non-acquired firms which can serve as a valid counterfactual. I thenestimate equation (2) on this matched sample, similar to Greenaway and Kneller (2007). Once again
I extend the basic model of equation (2) to allow for different acquisition impact depending on theownership statues of the takeover targets before the foreign acquisition and also depending onwhether the acquisition was motivated by either vertical or horizontal motives. To do so, I replace
the dummy variable Acq jt in equation (2) with four dummy variables, vertical acquired Swedish

MNEs, vertical acquired Swedish non-MNEs, horizontal acquired Swedish MNEs and horizontal
acquired Swedish non-MNEs. Moreover, to investigate the dynamic pattern of the post-acquisition
wage and productivity effect, I replace the four interaction variables for the whole post-acquisition
period with year-by-year interaction variables. Furthermore, since the matching procedure did not
reduce all the differences between acquired and non-acquired (matched) firms, as shown in Table

A2, I estimate the modified equation (2) with a firm-fixed effect model and control for a vector offirm characteristics such as capital-labor ratio, share of female workers, high-skill intensity and firmsize. Table 6 reports the results.
The matched sample in model (1) (column (i), (iv) (vii) and (ix)) is generated using the probit
model described in the Appendix, Table A1, column (i) and the matched sample in model (2) and(3) are generated using the probit model in Table A1 column (ii) and (iii), respectively. The DiD
estimators indicate that foreign acquisition have had, three and five years after acquisition, no
effects on wages in acquired firms (Swedish MNEs and non-MNEs). The results appear to be robust
depending on whether the foreign acquisition was motivated by vertical or horizontal motives.
The results of the productivity effect in the post-acquisition years are reported in the three lastcolumns of Table 6. The result indicates that vertical foreign acquisitions have had a positive effecton productivity growth in the years following takeovers. Three years after the acquisition the
productivity in targeted Swedish MNEs and non-MNEs seems to have grown by almost 3 and 2
percent more as compared to non-acquired firms. The productivity seems also to continue to growfive years after the acquisition. The difference in productivity growth between acquired and nonacquired firms is between 1 and 2 percent five years after the acquisition. There is however no14

significant impact on productivity from horizontal foreign acquisition, neither in targeted Swedish
MNEs or in targeted Swedish non-MNEs.

Table 8 here

5.

Conclusions

This paper has studied the effect of foreign acquisition on wages and productivity in the years
following a takeover by using unique detailed firm-level data for the Swedish manufacturing during
the 1990s. The distinct advantage of my data over the previous literature is that I can categorize all
the domestic firms into being domestic multinationals with affiliates abroad or domestic nonmultinationals. This means that I can allow the acquisition effect to differ depending on whether thetargeted firms were domestic multinationals or non-multinationals before the foreign takeover. Thisis an important dimension since the acquisition effect on firm performance may differ whether thetarget firms are multinational or not due to their ex-ante different characteristics as highlighted by,for example Helpman et al. (2004). Another distinct advantage of my data is that I can separate theforeign acquisition into being either horizontal or vertical acquisition. This means that I’m able toseparate the effects of foreign acquisition on targets depending on these two motives.
The results indicate that these two distinctions are indeed important. Foreign acquisitions seems tohave no effects on wages neither in targeted Swedish MNEs or in Swedish non-MNEs and neither if
the acquisition was motivated by vertical or horizontal motives. However, the results indicate thatboth targeted Swedish MNEs and non-MNEs have better growth in TFP after vertical foreignacquisition only but no such impact from horizontal foreign acquisition.
Based on these findings, there are important implications of this study. Firstly, the result gives nosupport to the strong fears that foreign acquisitions may have a detrimental effect on the targetedfirms’ performance. If anything, a foreign acquisition appears to have positive or neutral effects on
wage and productivity growth. Secondly, it is important to consider heterogeneity in the acquisition
impact, either by separating the different targets or by separating the acquisition motives, since not
all firms benefit equally from foreign takeovers and not all the acquisition motives have the same
effects.

15

References[1]

Bandick, R. and Karpaty, P. (2008), Foreign acquisition and employment effects in Swedish
manufacturing. Chapter 2 in Bandick, R. (2008), Multinationals, employment and wages.
Microeconomic evidence from Swedish manufacturing. Örebro Studies in Economics.

[2]

Becker, S. and Ichino, A. (2002), Estimation of average treatment effects based on
propensity scores. The Stata Journal, 2, 358-377.

[3]

Bernard, A. and Sjöholm, F. (2003), ‘Foreign owners and plant survival’, NBER working
paper 10039.

[4]

Betrand, O. and Zitouna, H. (2005), Domestic versus Cross-Border Acquisitions: WhichImpact on the Target Firms.Performance? Applied Economics, Taylor and Francis Journals,
vol. 40(17).

[5]Blundell, R. and Costas Dias, M. (2000), Evaluation methods for non-experimental data.
Fiscal Studies, 21, 427-468.

[6]

Conyon, M., Girma, S., Thomson, S. and Wright, P. (2002), The productivity and wage
effects of foreign acquisition in the United Kingdom. Journal of Industrial Economics, 50, 85102.

[7]

Doms, M. and Jensen, B. (1998), Comparing wages, skills, and productivity between
domestically and foreign-owned manufacturing establishments in the United States, in
Baldwin, R, Lipsey, R. and Richardson, D. (1998), Comparing wages, skills, and productivity
between domestically and foreign-owned manufacturing establishments in the United States.
Chicago: University of Chicago press.

[8]

Dunning, J. (1977), Trade, location of economic activity and the MNE: A search for an
eclectic approach, in Ohlin, B, Hesselborn, P-O. and Wijkman, P-M. (eds.), The international
allocation of economic activity. London: Macmillan.

[9]

Girma, S. and Görg H. (2006). ‘Multinationals’ productivity advantage: Scale or
technology?’ mimeo, University of Nottingham.

[10] Girma, S. and Görg H. (2007), Evaluating the foreign ownership wage premium using
difference-in-differences matching approach. Journal of International Economics, 72, 97-112.
[11] Golub, S. (2003), ‘Measures of restrictions of inward foreign direct investment for OECD
countries’, OECD Economic Studies, 36, 86-116.
[12] Greenaway, D. and R. Kneller (2007), Firm heterogeneity, exporting and foreign direct
investment', The Economic Journal . Vol. 117, Issue 517, pp. F134-161.
[13] Hansson, P., Karpaty, P., Lindvert, M., Lundberg, L., Poldahl, A. and Yun, L. (2007),‘Svenskt näringsliv i en globaliserad värld (Swedish business sector in a globalized
world) ’, ITPS A2007:004.

16

[14] Heckman, J., LaLonde, R. and Smith, J. (1999), The economics and econometrics of active
labor market programs, in Ashenfelter, O. and Card, D. (eds.), Handbook of labor economics.
Volume 3A. Amsterdam: North-Holland.
[15] Helpman, E. (2006), Trade, FDI, and the organization of firms, Journal of Economic
Literature, 94, 589-630.
[16] Helpman, E., Melitz, M. and Yeaple, S. (2004), Export versus FDI with heterogeneous firms.
American Economic Review, 94, 300-316.
[17] Heyman, F., Sjöholm, F. and Gustavsson Tingvall, P. (2007), Is there really a foreign
ownership wage premium. Journal of International Economics, 73, 355-376.
[18] Huttunen, K. (2007), The effect of foreign acquisition on employment and wages:
Evidence from Finnish establishments. Review of Economics and Statistics, 89, 497-509.
[19] Hymer, S. (1960), The international operations of national firms: A study of direct
investment. MIT Ph.D. thesis, published 1976, Cambridge: MIT press.
[20] Ilmakunnas, P. and Maliranta, M. (2004), Foreign Medicine: A Treatment Effect Analysis of
the Productivity Effects of Foreign Ownership.. Journal of Applied Economics Quarterly,Vol. 50 No. 1 (2004).
[21] Karpaty, P. (2007) Productivity Effects of Foreign Acquisitions in Swedish Manufacturing:
The FDI Productivity Issue Revisited. International Journal of the Economics of Business, vol14(2).
[22] Levinsohn, J. and Petrin, A. (2003), Estimating Production Functions Using Inputs toControl for Unobservables. Review of Economic Studies, Vol. 70(2), No. 243.
[23] Leuven, E. and Sianesi, B. (2003), PSMATCH2: Stata module to perform full
Mahalanobis and propensity score matching, common support graphing, andcovariate imbalance testing. Available at http://ideas.repec.or g/c/boc/bocode//s432001.html.
[24] Malmberg, A. and Sölvell, Ö. (1998). Spelar det någon roll? Om ökat utlandsägande i svenskt
näringsliv. (Does it matter? About increased foreign ownership in the Swedish businesssector) Report from ISA’s (Investment in Sweden Agency) Council of Economic Advisors.
[25] Markusen, J. (2002), Multinational firms and the theory of international trade.
Cambridge: MIT-press.
[26] Martins, P. (2004), Do foreign firms really pay higher wages? Evidence from different
estimators. IZA discussion paper 1388.
[27] McGuckin, R. and Nguyen, S. (2001), The impact of ownership changes: A view fromlabor markets, International Journal of Industrial Organization, 19, 739-762.

17

[28] Modén, K.M. (1998), Foreign Acquisitions of Swedish companies - effects on R&D and
Productivity. ISA 1998/2. Stockholm.
[29] Rosenbaum, P. and Rubin, D.B. (1983), The central role of the propensity score in
observational studies for causal effects, Biometrika, 70, 41-55.
[30] Salis, S. (2008), Foreign Acquisition and Firm Productivity: Evidence from Slovenia. The
World Economy, Vol. 31, Issue 8.8[31] Stiglitz, J. (1987), The causes and consequences of the dependence of quality on price.
Journal of Economic Literature, 25, 1-48.
[32] Woolridge, J.M. (2002), Econometric analysis of cross-section and panel data.
Cambridge: MIT press.

18

Table 1

Year
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002

Table 2

Number of firms and employment shares in Swedish manufacturing,
1993-2002.

Foreign MNEs
Firms
Employment(Percent)
Percent
347(13.1)
19.2
374(13.5)
19.9
395(13.4)
20.6
443(13.9)
24.0
487(14.8)
24.4
513(14.9)
25.8
538(15.8)
31.4
578(16.6)
35.3
640(18.2)
40.9
654(19.1)
42.0

Swedish MNEs
Firms
Employment(Percent)
Percent
608(22.9)
50.4
622(22.4)
52.3
604(20.4)
50.6
556(17.5)
46.7
551(16.8)
48.9
556(16.1)
46.4
587(17.3)
38.8
605(17.4)
35.7
591(16.8)
30.2
606(17.7)
31.1

Non-MNEs
Firms
Employment(Percent)
Percent
1699(64.0)
30.4
1783(64.2)
27.8
1955(66.2)
28.8
2180(68.6)
29.3
2247(68.4)
26.7
2380(69.0)
27.8
2273(66.9)
29.8
2297(66.0)
29.0
2278(64.9)
28.9
2165(63.2)
26.9

Frequency of foreign acquisitions by year, 1993-2002.

Acquired Swedish
MNE
Acquired Swedish
Non-MNE
Total

1994
2
(5.0)
38
(95.0)
40

1995
8(22.9)
27(77.1)
35

1996
53.2
(54.4)
37(46.8)
79

1997
9(26.5)
25(73.5)
34

19

1998
8
(27.6)
21(72.4)
29

1999
18(40.0)
27(60.0)
45

2000
7(14.3)
42(85.7)
49

2001
6
(6.3)
89
(93.7)
95

2002
13(22.4)
45(77.6)
58

94-02
113
(24.4)
351(75.6)
464

Table 3

Differences in means between foreign-acquired firms and non-acquired firms in the
period 1993-2002.

Variable

T = −1
Difference(t-ratio)

Acquired vs. non-acquired firms
T =0
T =1
T =2
Difference Difference Difference(t-ratio)(t-ratio)(t-ratio)

T =3
Difference(t-ratio)

Employment277(6.65)***
277
626(7.12)***

286(6.66)***
286
727(6.78)***

323(6.75)***
323
784(6.09)***

329(6.85)***
329
647(5.01)***

333(7.01)***
333233(2.28)**

lnTFP

0.55
(10.02)***0.50(9.72)***

0.42(8.43)***

0.46(9.15)***

0.46(8.73)***

Capital-labor ratio

150(2.41)***

138(2.46)***

146(2.48)***

164(2.49)***

165(2.46)***

Skill intensity

5.4(5.13)***

5.5(5.60)***

5.4(5.73)***

5.0(5.23)***

5.1(5.26)***

Average wage

26
(7.48)***

26(7.45)***

27(8.95)***

25(7.94)***

23(6.93)***

Wages: skilled71(9.72)***

68(9.51)***

64(9.52)***

61(9.01)***

55(7.48)***

Wages: less-skilled

19(7.10)***

19(7.06)***

19(7.78)***

18(7.46)***

17(6.41)***

Sales

Observations
Acquired firms
192
192
192
192
192
Non-acquired firms
3,659
3,659
3,659
3,659
3,659
Notes: Sales is in million SEK. Wages and capital-labor ratios are in thousand SEK. Skill intensity and share of
employees with a post-secondary education, are in percentages. TFP is calculated via the Levinsohn-Petrin (2003)
method.

Table 4

Difference-in-difference (DiD) estimator.

Acquired firms

Beforeacquisition
β 0 + β1Non-acquired firms

β0

Difference between acquired
and non-acquired firms

β120

After acquisition

Difference

β 0 + β1 + β 2 + β 3
β0 + β2
β1 + β3

β 2 + β3
β2
β3

Table 5

Post-acquisition effect on wages and productivity, instrumental variable approach.

Estimation (1)Foreign acquisition
Observation
Estimation (2)Foreign acquisition

Average waget+3
Model(1) Model(2) Model(3)
(i)
(ii)
(iii)
0.008
0.006
0.001
(3.58)*** (2.88)***(0.70)

Average skilled wage t+3
Model(1) Model(2) Model(3)
(iv)
(v)
(vi)
0.019
0.014
0.011
(3.18)*** (2.74)***(0.70)

Average less-skilled wage t+3
Model(1) Model(2) Model(3)(vii)(viii)
(ix)
0.003
0.004
0.002
(0.62)(0.80)(0.53)

Model(1)(x)
0.088(4.12)***

TFP t+3
Model(2)(xi)
0.092(4.49)***

Model(3)
(xii)
0.032
(2.33)***

13,47013,47013,47013,47013,47013,47013,470

Average skilled wage t+5
0.005
0.007
-0.003(0.71)(1.13)(0.86)

Average less-skilled wage t+5
0.001
0.002
-0.005(0.11)(0.42)(1.03)

0.045(3.70)***

TFP t+50.022(2.13)**

0.039(5.48)***

8,207

8,207

8,207

8,207

8,207

8,207

Average skilled wage t+3
0.014
0.012
0.009
(2.89)***(2.41)**(1.82)*

Average less-skilled wage t+3
0.002
0.002
0.002
(1.64)(1.55)(1.55)

0.035(2.91)***

TFP t+30.040(2.26)**

0.023(2.40)**

0.002(0.51)

13,47013,470

Average waget+5
0.002-0.002(0.60)(1.13)
8,207

8,207

13,47013,470Observation

8,207

Estimation (3)Vertical acquired
Swedish MNE

0.002(1.88)*

Vertical acquired
Swedish non-MNE

0.002(1.66)*

0.002(1.49)

0.001(0.01)

0.006(1.05)

0.004(0.83)

0.001(0.07)

0.001(0.87)

0.001(0.63)

0.002(1.46)

0.031(2.20)**

0.036(2.35)**

0.019(1.83)*

Horizontal acquired
Swedish MNE

0.001(0.85)-0.001(0.28)

0.001(1.27)

0.001(0.04)

0.001(1.43)

0.001(0.06)

0.001(1.10)-0.001(0.17)

0.001(1.55)

0.010(1.57)

0.009(1.30)

0.006(1.41)

Horizontal acquired
Swedish non-MNE

0.001(2.15)**

0.001(2.19)**

0.001(0.38)

0.001(0.31)

0.001(0.01)

0.001(0.13)

0.001(2.23)**

0.001(1.71)*

0.001(0.13)

0.014(1.28)

0.019(1.37)

0.011(1.04)

Estimation (4)Vertical acquired
Swedish MNE-0.001(0.58)

Average skilled wage t+5-0.004-0.004-0.004(0.53)(0.51)(0.75)

Average less-skilled wage t+5-0.001-0.0020.002(0.49)(0.86)(0.88)

0.027(2.07)**

TFP t+50.010(2.04)**

0.018(2.38)**

Vertical acquired
Swedish non-MNE-0.001(0.41)-0.001(0.48)-0.003(0.99)-0.006(0.82)-0.003(0.50)-0.008(1.24)-0.001(0.03)-0.001(0.54)-0.001(0.09)

0.011(1.89)*

0.012(1.65)*

0.010(2.12)**

Horizontal acquired
Swedish MNE-0.001(0.09)-0.001(0.47)-0.001(1.28)

0.001(0.63)

0.001(2.31)**

0.001(0.12)

0.001(0.76)

0.001(0.05)

0.001(1.20)

0.009(1.23)

0.007(1.03)

0.003(0.80)

Average waget+3
0.002
0.002
(1.82)*(1.52)

Average waget+5-0.0010.001(0.64)(0.39)

8,207

8,207

13,4708,207

Horizontal acquired
0.002
0.001
0.001
0.001
0.002
0.001
0.002
0.001
0.001
0.008
0.007
0.006
Swedish non-MNE(2.12)**(2.08)**(1.35)(0.29)(1.44)(0.01)(1.97)**(2.08)**(1.21)(1.19)(0.94)(1.09)
Notes: Standard errors within the parentheses are bootstrapped. ***, **,* indicate significance at the 1, 5 and 10 percent levels, respectively. Estimations in Model 1
use an instrument generated from the probit regression reported in Table A1, column (i). The estimation in Model 2 uses an instrument generated from column (ii) in
Table A1; estimations in Model 3 use an instrument from column (iii) in Table A1. In all the estimates, I control for changes in firm-specific factors similar to theseincluded in Table 4. The Hausman tests, not reported but available upon request, reject the assumption of exogeneity of the acquisition dummy.

21

Effects of foreign acquisition on post-acquisition average wage and TFP. DID on matched sample with firm fixed effect.

Table 6

Average wage
Model(1) Model(2) Model(3)
(i)
(ii)
(iii)
0.001
0.004
-0.002[0.07][0.42][0.21]

Average skilled wage
Model(1) Model(2) Model(3)
(iv)
(v)
(vi)
0.017
0.011
0.015
[0.57][0.37][0.57]

Average less-skilled wage
Model(1) Model(2) Model(3)(vii)(viii)
(ix)
0.002
0.004
0.001
[0.27][0.46][0.03]

Model(1)(x)
0.030[2.41]**

TFP
Model(2)(xi)
0.025[2.15]**

Model(3)
(xii)
0.023
[2.11]**

SMNEi × Ver _ Acq j × Aftert + 5

0.002[0.20]

0.008[0.78]-0.011[0.98]

0.046[1.32]

0.044[1.24]

0.035[1.09]

0.003[0.28]-0.006[0.53]

0.012[1.07]

0.021[2.13]**

0.011[1.99]**

0.014[2.01]**

NonMNEi × Ver _ Acq j × Aftert +3

0.009[1.25]

0.010[1.46]

0.006[0.66]

0.010[0.43]

0.013[0.56]

0.020[0.79]

0.009[1.25]

0.011[1.47]

0.005[0.57]

0.024[2.46]**

0.022[2.33]**

0.019[2.08]**

NonMNEi × Ver _ Acq j × Aftert +5

0.010[1.08]

0.001[0.13]-0.009[0.81]

0.049[1.72]*

0.045[1.54]

0.032[1.06]-0.002[0.19]-0.010[1.10]

0.013[1.18]

0.011[2.20]**

0.010[2.17]**

0.009[1.97]**

SMNEi × Hor _ Acq j × Aftert + 3

0.002[0.06]

0.003[0.07]

0.002[0.04]

0.011[0.10]

0.012[0.10]

0.010[0.23]

0.020[0.53]

0.023[0.63]

0.022[0.49]

0.010[1.51]

0.018[1.58]

0.009[1.59]

SMNEi × Hor _ Acq j × Aftert + 5

0.007[0.07]

0.009[0.08]-0.009[0.20]

0.059[0.49]

0.057[0.57]

0.003[0.03]

0.004[0.11]-0.004[0.10]

0.004[0.09]

0.011[1.62]

0.017[1.61]

0.014[1.56]

NonMNEi × Hor _ Acq j × Aftert +3-0.001[0.01]

0.004[0.12]

0.001[0.05]

0.045[0.42]

0.069[0.63]

0.038[0.42]-0.007[0.22]-0.003[0.09]

0.005[0.57]

0.011[1.50]

0.018[1.18]

0.010[1.48]

NonMNEi × Hor _ Acq j × Aftert +5

0.008[0.23]

0.002[0.08]-0.008[0.25]

0.038[0.36]

0.041[0.38]

0.061[0.66]

0.008[0.24]-0.001[0.03]-0.009[0.26]

0.010[0.24]

0.021[0.92]

0.028[0.60]

Firm controls

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

R 2 within

0.700

0.719

0.735

0.215

0.185

0.259

0.673

0.685

0.712

0.049

0.034

0.039

2

0.287

0.379

0.414

0.022

0.066

0.049

0.291

0.332

0.374

0.031

0.198

0.004

0.405
0.468
0.484
0.081
0.116
0.129
0.412
0.444
0.467
0.031
0.091
R 2 overall
Observations
4,823
4,823
4,823
4,823
4,823
4,823
4,823
4,823
4,823
4,823
4,823
Notes: As firm controls I use capital-labor ratio, share of female workers, high-skill intensity and firm size. Square brackets [ ] give White’s heteroskedasticityconsistent t statistics. The matched sample in Model (1) is generated using the probit model in Table A1, column (i). The matched sample in Model (2) and Model (3)are generated using the probit model in Table A1, column (ii) and column (iii), respectively.

0.002

SMNEi × Ver _ Acq j × Aftert +3

R

between

224,823

Appendix A
The probit model
The instrumental variable is constructed as the predicted value of the dependent variable from a
probit regression for the probability of foreign takeover, similar to McGuckin and Nguyen (2001)
and Conyon et al. (2002). The probit model isp ( Acq jt = 1) = F ( X jt −1 , Di , Dt )(A.1)

where X is a vector of firm characteristics in t-1. Di and Dt control for fixed industry and timeeffects. The vector of firm characteristics in equation (A.1), in the first instance, includes laborproductivity in firm j, a dummy variable indicating whether the firm is a Swedish MNE or not,current employment size (relative to the industry mean), skill intensity, firm age, age-squared and ameasure of foreign presence in the industry. The latter measure captures potential spillover effects
in an industry.
The results of estimating equation (A.1) are reported in Table A1. I find that skill-intensive and highproductivity firms are more likely to be acquired by foreign firms. Moreover, firms in industries
with a large foreign presence are more often taken over. Finally, it appears that younger firms (nonlinear relationship), relatively large firms, and Swedish MNE firms have higher probabilities ofbeing targeted by foreign firms.
I also estimated alternative specifications of equation (A.1), including additional variables in the
probit estimation, to check whether my results depend on the process by which the instrument was
generated. These results are reported in columns (ii) and (iii) of Table A1. The estimations ofequation (1) in Table 5 and equation (2) in Table 6 are robust to this change in the instrument
generating specification.

23

The probit model – probability of foreign acquistion

Table A1
Variables

(i)

(ii)

(iii)

Labor productivity

0.125(2.75)***

0.022(0.47)

0.083(1.81)*

Swedish MNE

0.116(2.37)**

0.055(1.11)

0.040(0.78)

Relative employment

0.005(2.33)**-0.002(0.65)-0.001(0.45)

Skill intensity

0.138(4.75)***

0.141(4.64)***

0.127(4.28)***

Age−0.052(4.81)***−0.052(4.81)***−0.055(5.06)***(Age)20.001(3.91)***

0.001(3.59)***

0.001(3.75)***

Foreign presence

0.052(2.48)**

0.046(2.13)**

0.046(2.15)***

Capital intensity

0.087(6.17)***

Sales

0.028
(6.74)***

Year dummies
Yes
Yes
Yes
Pseudo R2
0.037
0.046
0.050
LR chi2
139.58177.57181.22
Observations
23,931
23,931
23,931
Notes: The dependent variable Acq jt = 1 if a domestically owned firm in year t − 1 becomes foreign-owned in year t.
z-statistics are within parentheses. The explanatory variables are, with the exception of age, age2 and relative
employment, firm-specific characteristics in year t − 1 . Relative employment is firm employment relative to mean firm
employment at the industry level. Labor productivity is value added per employee and skill intensity is the share of
employees with post-secondary education at the firm level. The share of foreign employment at the industry level(SNI92 2-digit level) is a proxy of foreign presence in the industry.

24

Table A2

Differences in means between foreign-acquired firms and non-acquired firms in the
period 1993-2002. Matched sample.
Acquired vs. non-acquired firms
T =0
T =1
T =2
Difference Difference Difference(t-ratio)(t-ratio)(t-ratio)

T =3
Difference(t-ratio)

Variable

T = −1
Difference(t-ratio)

Employment99(0.98)

88(0.84)

126(1.04)

139(1.15)

156(1.32)

Sales

380(1.46)

424(1.39)

462(1.29)

280(0.92)-166(0.73)

lnTFP

0.27(4.73)***

0.19(3.59)***

0.11(2.03)**

0.14(2.65)**

0.18(3.10)***

Capital-labor ratio-21(0.09)

75(1.15).

81(1.13)

113(1.86)*

109(1.69)*

Skill intensity

1.9(1.56)

2.0(1.69)*

1.7(1.43)

1.2(1.06)

1.4(1.22)

Average wage

19
(7.37)***

19(5.82)***

21(7.60)***

16(5.20)***

13(3.29)***

Wages: skilled

39(6.76)***

35(6.26)***

34(6.09)***

28(4.65)***

19(2.13)**

Wages: less-skilled15(6.24)***

16(5.03)***

18(7.64)***

14(4.82)***

10(3.23)***

181
372

181
372

181
372

181
372

181
372

Observations
Acquired firms
Non-acquired firms

25