Home Firm Performance After ForeignInvestments and Divestitures

Dirk Engel1,2 and Vivien Procher2,31University of Applied Sciences Stralsund, Stralsund, 2Rheinisch-Westf€alisches Institut f€ur

Wirtschaftsforschung (RWI), Essen, and 3Jackst€adt Center of Entrepreneurship and Innovation Research,

Schumpeter School of Business and Economics, University of Wuppertal, Wuppertal

1. INTRODUCTION

EXPORTING and foreign direct investment (FDI) can be seen as alternative strategies to

serve foreign markets, and thus, switching from export to FDI might reduce home-based

export activities. Consequently, policymakers worry that FDIs imply a significant relocation

of jobs from home to host countries. However, existing papers do not provide substantial

empirical confirmation for any negative effects of FDI on home employment (e.g. Barba

Navaretti and Castellani, 2008; Becker and Muendler, 2008; Desai et al., 2009). Therefore,

this paper investigates the extent to which the FDI – export relationship can illuminate this

trend. Among others Head and Ries (2004) argue that the location of different stages of pro-

duction in different countries (i.e. vertical specialisation) and home centralisation of certain

products may matter for firms which in turn would point towards a positive association

between FDI and exporting.

Based on a large database for French firms and applying propensity score matching com-

bined with a difference-in-difference (DiD) estimator, we show that FDI and exporting often

constitute complementary activities. To the authors’ knowledge, there is no study that analy-

ses the FDI – export relationship and the relationship between FDI and domestic employment

simultaneously. While this relationship is not homogeneous across firms, any study should

address the important role of moderating factors like industry affiliation. We provide some

empirical evidence by differentiating between firms in high-tech and low-tech industries. The

imitation of knowledge-intensive products might have great consequences for the comparative

advantage of firms in high-tech industries, so that the latter might be more inclined to opt for

vertical specialisation and home centralisation of production processes. In contrast, firms in

low-tech industries might prefer to substantially replicate and relocate production process to

low-cost countries. As a result, we expect export activity of firms in high-tech industries are

affected to a larger extent by the FDI decision than firms in low-tech industries.

While many empirical studies analyse the role of investments and acquisitions on home

plant performance, we fail to detect any study which addresses the effects of divesting from

abroad on home firm employment, turnover and export activity. The meta-analysis of Lee and

Madhavan (2010) clearly confirms this research gap. Existing papers focus either on financial

accounting measures (e.g. return on investment) or stock price changes due to foreign divesti-

tures announcements. Driven by the globalisation of production processes, divestitures have

We would like to thank the anonymous referee who gave precise and helpful comments on an earlierversion sent to The World Economy. Furthermore, we appreciated the comments and suggestions madeby Christoph M. Schmidt. The financial support by the Ruhr Graduate School in Economics is gratefullyacknowledged.

© 2013 Blackwell Publishing Ltd., 9600 Garsington Road,Oxford, OX4 2DQ, UK and 350 Main Street, Maiden, MA 02148, USA. 1

The World Economy (2013)doi: 10.1111/twec.12068

The World Economy

become increasingly relevant in the last few decades. Moreover, business restructuring due to

the financial and economic crisis since 2008 will further raise the likelihood of divestitures in

the years to come. By analysing both the effects of investing abroad and divesting from

abroad, we finally provide a comprehensive analysis on the home performance of firms after

stepping in and out of foreign markets.

The remainder of the paper is organised as follows: Section 2 contains a brief review of

the FDI and divestiture literature with respect to firm performance. Section 3 describes the

data and methodological approach. Results are presented in Section 4. Section 5 presents the

conclusions drawn.

2. BACKGROUND

a. Effects of Investing Abroad

The debate of home market effects from FDI is often linked to the actual type of FDI.

Resource-seeking FDI might affect home plant output and employment negatively and pro-

ductivity positively in the short term, as some production processes are relocated to exploit

cost advantages at the foreign location. In the long term, however, positive effects on output

and employment based on reducing the cost of production may dominate which then allows

product prices to decrease and, thus, could induce higher demand at home. Furthermore,

extensive intra-firm trade between headquarters and foreign affiliates might curtail negative

effects of (partial) relocation when the firm prefers to concentrate some production stages

abroad (see Head and Ries, 2004).

Market-driven FDI with self-contained foreign production units might substitute some

home-based export activities so that domestic employment decreases. However, multinational

enterprises (MNEs) who concentrate on market-driven FDI are likely to exploit economies of

scale by accessing new markets, which in turn may have positive effects on the productivity

at home. Similarly, firms also experience performance gains through their exposure in foreign

markets (see the learning-by-exporting hypothesis e.g. Bernard and Jensen, 1999; Wagner,

2007; meta-analysis by Martins and Yang, 2009).

Recent empirical studies analyses intensively the effects of investing abroad on home

plant’s performance. Based on the extensive use of propensity score matching combined with

a DiD approach in the microeconometric programme evaluation (Heckman et al., 1998), this

kind of estimator has also received increasing attention in the FDI literature. Barba Navaretti

and Castellani (2008) apply this estimator and find significant positive effects of outward FDI

by Italian MNEs on turnover and productivity (TFP) at home, but the effect on employment

is insignificant. Based on a small sample of 47 German MNEs, Kleinert and Toubal (2007)

also observe an insignificant effect on employment and a significant increase in TFP in the

first year after investing abroad. J€ackle and Wamser (2010) use the same database and apply

Heckman’s (1978) parametric estimator for endogenous treatment effects. They find signifi-

cant positive effects of FDI on TFP for German MNEs up to three years after going abroad.1

For Japanese MNEs, Hijzen et al. (2007) observed a weak significant positive effect on

domestic factory TFP in the initial year and significant positive effects on output and employ-

1 Interestingly the OLS estimates are downward biased in this study which suggests that no significantdifferences in TFP growth and employment growth exist.

© 2013 Blackwell Publishing Ltd.

2 D. ENGEL AND V. PROCHER

ment in the following three years. The study of Becker and Muendler (2008) combines

German factorial level data with data about foreign affiliates to estimate the effect of employ-

ment expansion in foreign affiliates on domestic employment. The authors discover that the

probability of domestic worker separation is significantly reduced. In fact, the fear of policy-

makers that outward FDI relocates jobs from home to target countries is hardly supported in

any corresponding empirical studies.

A handful of papers consider host-country characteristics to estimate the effects of investing

abroad for resource- and market-driven FDI. Head and Ries (2003) look at the host countries

chosen by firms for their investments and classify them into low- and high-wage countries. The

authors argue that firms with investment in low-wage countries only follow resource-driven FDI

motives, whereas companies with investments in a wider range of low- and high-wage countries

follow a more horizontal pattern of FDI. Barba Navaretti et al. (2010) adopt the basic idea to

analyse the impact on TFP, turnover and employment at home for Italian and French MNEs.

Interestingly, the findings do not differ remarkably for outward investments in low-wage and

high-wage countries. TFP growth is significantly positive in Italy, whereas FDI of French firms

does not matter for TFP growth at home. Employment is neither significantly negative in France

nor in Italy. Similarly, Becker and Muendler (2008) do not detect any remarkable differences

across several host-country locations. In sum, there is hardly any evidence of a negative effect

of outward investments on home performance, in particular on home employment.

Many other papers explicitly address the relationship between FDI and exports. Standard

theory would predict that exporting and FDI are substitutes even if firms relocate or duplicate

home production to a foreign country without any kind of intra-firm trade. Head and Ries

(2004) argue that complementarity between FDI and export occurs when investing abroad is

linked with (i) vertical specialisation (exports of intermediate goods between the parent com-

pany and its foreign affiliates) and/or (ii) home centralisation of one product and foreign cen-

tralisation of another product. Here, home centralisation for firms becoming engaged in FDI

implies that they simultaneously increase the domestic production for products destined for

export markets. A further argument for complementarity can be derived from Krautheim

(2009). He introduces the term ‘export-supporting FDI’ which means that firms found retail

affiliates to sell products produced at home in a foreign market. In a recent study, Hering

et al. (2010) consider affiliate characteristics, to better distinguish between horizontal and ver-

tical FDI for Japanese MNEs. Affiliates with a high level of local purchases and high sales

back to Japan are defined as vertical FDI implying a high level of vertical specialisation. In

line with standard theoretical predictions of the ‘proximity-concentration trade-off’, the

authors observe that horizontal FDI substitutes exports from MNEs’ home country. In con-

trast, imports increase for MNEs with vertical FDI. The study further reveals that labour pro-

ductivity in Japanese parent companies increases when Japanese MNEs either start horizontal

FDI in high-income countries or vertical FDI in low-income countries. Nevertheless, a com-

prehensive study across all business sectors that simultaneously analyses the ‘FDI – export’

and the ‘FDI – home performance’ relationship is still non-existent.

We further expect that the extent of complementarity between FDI and export differs with

respect to firm’s strategy of home centralisation, based on their technological advantage. In

general, products of firms in high-tech industries are based on remarkable achievements in

R&D, in an attempt to create a sustainable technological advantage. Faced by the risk of

product imitation, firms may opt for home centralisation of high-tech products and vertical

specialisation to reduce this risk. Therefore, one might assume that firms in high-tech indus-

tries are more inclined to opt for home centralisation and vertical specialisation than firms in

© 2013 Blackwell Publishing Ltd.

HOME FIRM PERFORMANCE, FDI AND DIVESTITURES 3

low-tech industries. Recent empirical findings of Amador and Cabral (2009) support this

assumption. The authors show that vertical specialisation activities are more pronounced in

high-tech than low-tech industries. The empirical study of Stiebale (2010) also strengthens

this prediction. Applying an empirical framework that accounts for unobserved firm heteroge-

neity and the possible endogeneity of cross-border acquisitions, he shows that R&D activity

of acquirers in high-tech industries was intensified after an outward merger or acquisition,

compared with acquirers in low-tech industries.

b. Effects of Divesting from Abroad

While the literature intensively discusses the effects of investing abroad, there are not

many studies in the economics literature, which analyse the effects of foreign divestitures on

the home performance of enterprises. Foreign divestitures are characterised by a shut down or

selling assets of foreign operations (e.g. Benito, 1997). Following Hanson and Song (2003)

and Mathur et al. (2006), four main reasons for divesting are proposed: (i) eliminating nega-

tive synergies; (ii) raising cash to fund other investments; (iii) agency problems and (iv) a

positive difference between acquirer’s willingness to pay for the asset and its valuation by the

seller. With respect to foreign operations, negative synergies mainly arise when a foreign sub-

sidiary underperforms and resources have to be shifted from the mother company to the for-

eign subsidiary. Agency problems are mainly driven by managerial discretion. Insufficient

monitoring mechanisms as well as managerial incentive schemes to promote growth instead

of profitability, imply that managers tend to waste free cash flow for less profitable projects to

realise their own non-value maximising objectives (Jensen, 1986).

The empirical literature on the effects of divestitures either focus on accounting measures

like return on assets or market-based measures like cumulative abnormal returns (see Lee and

Madhavan, 2010 for details). With respect to the latter stock price changes prior to and after

the announcement of divestiture are analysed (see Cao et al., 2008 for a recent study). Given

that divestitures reduce negative synergies as well as agency costs, the headquarters has the

potential to increase its cash position. Hanson and Song (2003) empirically confirmed this

prediction. Divesting firms have significant lower returns on assets than matched control firms

in the two years before divestiture, but significant higher returns in the second and third year

after divestiture. Denis and Shome (2005) analysed 130 large asset downsizings between 1985

and 1994, and found that downsized firms achieve on average an 7.9 per cent increase in the

mean of operating income divided by book value of assets within three years after

downsizing.

The effects on employment and productivity might differ from effects on accounting mea-

sures. First, foreign divestitures can offer growth opportunities at headquarters when produc-

tion is shifted back home and foreign markets of previously divested foreign affiliates are

partly served from domestic factories. Based on 664 foreign divestiture announcements,

Mathur et al. (2006) did not find a significant reduction in foreign sales related to total sales,

between two years after and one year before announcements for firms with foreign divesti-

tures, in comparison with control firms without foreign divestitures. This finding supports the

view that these firms did not exit foreign markets completely.

Positive employment effects may also occur due to reduced negative synergies, debt over-

hang and agency problems. Mathur et al. (2006) noted that capital expenditures divided by

total assets are slightly higher for firms with foreign divestitures than for control firms. Thus,

domestic employment might increase after foreign divestitures. An empirical analysis can

© 2013 Blackwell Publishing Ltd.

4 D. ENGEL AND V. PROCHER

provide a more comprehensive understanding of average employment effects after foreign

divestitures.

3. DATA AND EMPIRICAL METHOD

a. Panel Structure

This paper utilises firm-level data from the European AMADEUS database which is

provided by Bureau van Dijk (BvD). The data collection by BvD is carried out by coun-

try-specific information providers, for example the credit insurer Coface Scrl in France.

These providers use published sources including annual reports and stock exchange infor-

mation. In addition, they contact companies directly to handle collection orders from com-

panies’ business partners (e.g. banks). The coverage ratio of AMADEUS data is 73.5 per

cent related to total sales of Sirene register which covers all French companies (see

INSEE, 2012).

Companies’ financial records are available for up to 10 years but information on the own-

ership and subsidiary structure is static and based on the latest annual report available in the

year of data compilation. Dynamics in the (foreign) subsidiary network can only be analysed

via the various updates of the AMADEUS database. We have access to six updates and focus

on changes in the international status of companies that take place between the years 2000

and 2002, 2002 and 2004, as well as 2005 and 2007, respectively. Consequently, we analyse

the post-entry and post-exit domestic performance of French exporters and MNEs that chan-

ged their status in 2001, 2003 or 2006.

Our data set is limited to unconsolidated firm-level accounts to analyse location- and

entity-specific performance effects. The data set includes companies of a wide range of

manufacturing and service industries.2 Table 1 provides an overview of the underlying

panel structure. The overall panel is unbalanced as the latest year for which key financial

data are available is 2010. Given the underlying data structure, the short-term analysis

(t + 1 and t + 2) is based on a larger sample of firms than the long-term analysis (t + 5

and t + 6).

We differentiate between two types of changers with exporting firms that become engaged

in FDI (i.e. new MNEs, DX-DI) and MNEs that divest all foreign affiliates to become pure

exporters (DI-DX). The number of observations, as depicted in Table 2, is obtained via probit

estimations with variables taken from the pre-change periods. In sum, the number of exporters

going abroad is much larger (884) than the number of MNEs that cease their foreign opera-

tions (279). In the majority of cases, a large pool of potential control firms (non-changers)

exists, which is a prerequisite for finding a comparable firm for each treated observation in

the subsequent matching procedure.

The number of firms used in the matching procedure and DiD analysis can be further

reduced if key performance variables are missing in the post-change period. Consequently,

the number of observations depends on the type of change, the year of change and the specific

2 Excluded from the analysis are the following industries (with the industry codes (NACE) in parenthe-ses): Agriculture, hunting and forestry (01, 02), fishing (05), mining and quarrying (10–14), managementactivities of holding companies (7,415), public administration and defence, compulsory social security(75) and activities of membership organisations (91). Values in the upper and lower 1st percentile of thedistribution are eliminated from the dataset in order to control for outliers and coding errors.

© 2013 Blackwell Publishing Ltd.

HOME FIRM PERFORMANCE, FDI AND DIVESTITURES 5

outcome variable.3 Therefore, the final sample size is reported with the results for the DiD

analysis in Tables 3–6 in Section 4.

b. Empirical Method

Given a firm changes its mode of internationalisation, we cannot observe the outcome of

the hypothetical situation of not changing, and thus, we are not able to calculate the economic

effect of a change in the internationalisation mode directly. Usually, it needs a group of ade-

quate control firms without mode change to run a precise estimation of the outcome for the

counterfactual situation. In this paper, we follow state-of-the-art methodology and combine

TABLE 1Panel Structure

Pre-change Change Post-change

t�2 t�1 t t + 1 t + 2 t + 3 t + 4 t + 5 t + 6

1999 2000 2001 2002 2003 2004 2005 2006 20072001 2002 2003 2004 2005 2006 2007 2008 20092004 2005 2006 2007 2008 2009 2010 – –

TABLE 2Number of Observations

Pre-change Year (t�1) 2000 2002 2005 Total

Foreign investment (FDI)DX-DI Treated 792 292 335 1,419DX Control 25,930 28,745 34,746 89,421D-DI Treated 273 115 160 548D Control 79,807 100,977 153,094 333,878Foreign divestmentDI-DX Treated 136 204 106 446DI Control 324 1,189 1,465 2,978DI-D Treated 96 96 66 258DI Control 350 1,297 1,191 2,838

Notes:(i) Changes in the internationalisation status can occur between 2000 and 2002, 2002 and 2004, 2005 and 2007, wherethe first year refers to the pre-change period (t�1). For example, firms in the DX-DI group with the pre-change year2000 were exporters (DX) in 2000 who became multinational enterprises (DI) by 2004. (ii) The number of observa-tions is obtained from probit models on pre-change variables. (iii) The control groups refer to the potential number offirms that can function as control observations in the matching procedure. (iv) ‘Total’ refers to firm-year observations.

3 In principle there are 36 different sample sizes due to two changing modes (upward D/DX-DI anddownward DI-DX/D), three changing years (2001, 2003 and 2006) and six outcome variables (exportturnover, export share, number of employees, operating turnover, labour productivity and TFP). Valuesin the upper and lower 1st percentile of the distribution are eliminated from the dataset in order to con-trol for outliers and coding errors.

© 2013 Blackwell Publishing Ltd.

6 D. ENGEL AND V. PROCHER

the propensity score matching to construct the sample of adequate control firms with the DiD

estimator (e.g. Heckman et al., 1998, 1999; Blundell and Costa Dias, 2000, 2002) to estimate

the average treatment effect on the treated (ATT).

As the number of observables used in the matching process increases, it becomes rather

difficult to find a suitable match for every firm; furthermore, every unmatched firm is tanta-

mount to data loss. The propensity score method suggested by the pioneer work of Rosen-

baum and Rubin (1983) constitutes a helpful solution by computing the probability of mode

change conditional on observables by applying a logit or probit estimation. We implement a

nearest neighbour matching with replacement to match each treated firm with one non-treated

firm with the closest probability of mode change.4 This procedure implies that a non-treated

firm can be matched to more than one treated firm. Therefore, a correction for standard errors

to draw conclusions on statistical inference is required. We follow Lechner (2001) and apply

his estimator for an asymptotic approximation of the standard errors.

When the matching method is completed, we can then apply DiD estimator to calculate

the ATT as follows:

ATTDiD ¼ E½Y1i;tþk � Y1

i;t�1� � E½Y0i;tþk � Y0

i;t�1�:The DiD estimator evaluates the average performance E½Y1

i;tþk � Y1i;t�1� of treated firms

between the year before (t�1) and k years after a mode change against the average perfor-

mance E½Y0i;tþk � Y0

i;t�1� for matched non-treated firms.

c. Outcome and Control Variables

All firm-specific state variables used in the probit model to explain changes in the mode of

internationalisation are taken from the pre-change period, t�1. Many theoretical and empirical

papers (e.g. Roberts and Tybout, 1997; Helpman et al., 2004) emphasise the important role of

basic firm characteristics like the number of employees, operating revenue, age and productiv-ity for bearing the sunk costs of investing abroad. We further include previous export turnoverand export share (export to total operating turnover), which might approximate international

experience and attractiveness of foreign markets. The productivity measures used in the probit

models refer to labour productivity, defined as operating revenue per employee. All these

quantitative variables are included as values in logarithm.5

A growing number of studies point out that multiunit and multinational characteristics as

well as ownership characteristics can also affect firm’s mode of internationalisation (e.g.

Roper et al., 2006; Bernard and Jensen, 2007; Greenaway et al., 2007). Therefore, firms’

ownership structure is used as a proxy for underlying strategic interests of its owners and is

captured by the dummy variables corporate shareholder, financial shareholder, state share-holder, individual shareholder and foreign shareholder for non-French investors. Only owners

with an ownership share of 10 per cent or more are taken into account to assure an effective

4 The matching procedure is carried out using software package psmatch2 in STATA 12 (see Leuvenand Sianesi, 2003).5 In previous estimations we also took into account the growth rate of employees, productivity and(export) turnover to check for the role of firm’s growth path. Since we detect no significant coefficientestimates for growth rates we decided to leave out these variables in the final estimations to prepare ourmatched samples.

© 2013 Blackwell Publishing Ltd.

HOME FIRM PERFORMANCE, FDI AND DIVESTITURES 7

voice in the management of a firm. The organisational structure is further accounted for by

the number of domestic subsidiaries.Financially constrained firms might be less likely to enter (Chaney, 2005) and more likely

to leave foreign markets. Companies can fail to finance their internationalisation because of a

liquidity shortage. Thus, following recent empirical papers on foreign market participation

(Greenaway et al., 2007; Stiebale, 2011), we include a liquidity ratio defined as the difference

of current assets and current liabilities to total assets.

Markusen (1995) highlights the positive correlation between the importance of intangible

assets in industries and the economic importance of MNEs. The ratio of intangible fixed assets to

tangible fixed assets is used as a proxy for the knowledge capital because no direct information is

available on corporate R&D expenses. Finally, up to 28 industry dummies based on the two-digit

NACE classifications attempt to capture any remaining industry-specific heterogeneity.

For evaluating the post-entry as well as post-exit performance, we concentrate on six out-

come variables. The main variables of interest are export share (i.e. export to total operating

revenue) and export turnover to analyse the extent to which exports serve as substitutes or

complements of FDI. Additionally, employment, operating revenue, labour productivity and

total factor productivity are taken into account.6 With exception of the export share, we com-

pute and compare growth rates of variables between the treatment and non-treatment group.

The computation of growth rates follows Evans (1987) approach by assuming an exponential

growth trend. Annual average growth rates are calculated as the difference between the loga-

rithm of outcome variables in any year t + k (with k � 1) and the pre-switching year t�1,divided by the number of years between t + k and t�1.

4. RESULTS

Separate probit regressions are carried out for each switching mode and year to obtain

matched samples of treated and suitably non-treated firms. In sum, we fail to detect any

significant differences between both groups of firms before the treated firms change the mode

of internationalisation.7 This in turn allows interpreting differences in outcome variables as

result of switching the mode of internationalisation.

a. Investing Abroad

The results from the DiD estimation for treated firm, which invest abroad for the first time,

are presented in Tables 3 and 4. The number of firm observations decreases over time as

complete outcome records are not available for all post-change periods.8 Our main variables

of interest are export turnover and export share. According to results depicted in Table 3, new

MNEs are affected by a significant increase in the absolute export turnover compared with

domestic firms and exporters that, in the same time frame, did not become engaged in FDI.

6 TFP is obtained by applying the STATA command (levpet). The TFP value corresponds to the residualobtained from a firm-specific Cobb-Douglas production function. In contrast to labour productivity, TFPhas no obvious scaling or natural base values thereby impeding a direct interpretation (see Levinsohnet al., 2003 for details).7 The results for the probit estimations and balancing tests are available on request.8 Robustness checks are carried out for firms with a complete outcome record in all post-changeperiods.

© 2013 Blackwell Publishing Ltd.

8 D. ENGEL AND V. PROCHER

The export turnover is already 47.4 percentage points higher in the first year after switching

and increases to 85.3 percentage points after six years compared with the year before invest-

ing abroad. Since the annual growth rate in operating revenues is much lower, new MNEs

display a higher export share growth in all post-change periods, ranging from 2.1 to 4.8 per-

centage points. This persistent and accelerating rise is remarkable because treated firms

already display an initial ratio of exports to total sales of around 30 per cent in t�1. Overall,

these findings suggest that exporting and FDI are complements rather than substitutes in inter-

national trade, including manufacturing and services sectors. The complementarity even holds

TABLE 3The Effect of Becoming Engaged in FDI on Firm’s Home Performance (D/DX-DI)

Outcome Variable xt + k–xt�1 Treated Firms Diff-in-diff t-Values

Export turnover t + 1 1,955 0.4735*** 4.780t + 2 1,894 0.5460*** 5.161t + 3 1,859 0.6127*** 5.290t + 4 1,557 0.8174*** 5.802t + 5 1,402 0.7522*** 4.564t + 6 1,389 0.8525*** 4.965

Export share t + 1 1,952 0.0211*** 3.701t + 2 1,895 0.0288*** 4.660t + 3 1,859 0.0324*** 4.659t + 4 1,555 0.0486*** 5.595t + 5 1,404 0.0428*** 4.335t + 6 1,389 0.0484*** 4.714

Operating turnover t + 1 1,952 0.0811*** 4.206t + 2 1,895 0.0924*** 4.155t + 3 1,859 0.1098*** 3.805t + 4 1,555 0.1257*** 3.235t + 5 1,404 0.1464*** 3.084t + 6 1,389 0.1804*** 3.373

Employment t + 1 1,712 0.0252 1.391t + 2 1,528 0.0460* 1.919t + 3 1,537 0.0584** 2.249t + 4 1,318 0.0508 1.456t + 5 1,032 0.0599 1.262t + 6 1,232 0.0685 1.471

Labour productivity t + 1 1,709 0.0415** 2.160t + 2 1,527 0.0258 1.251t + 3 1,534 0.0422* 1.809t + 4 1,317 0.0436 1.428t + 5 1,032 0.0713* 1.728t + 6 1,232 0.1152*** 2.762

TFP t + 1 1,323 �0.0534 0.240t + 2 1,165 �0.0624 0.233t + 3 1,187 0.0149 0.059t + 4 1,034 0.0420 0.138t + 5 833 �0.0082 0.021t + 6 956 �0.0730 0.204

Notes:(i) Reported are the results for the difference-in-difference estimations with xt + k–xt�1, where t = change period andk takes the values 1–6. (ii) The t-values are reported and *p < 0.10, **p < 0.05, ***p < 0.01.(iii) FDI, foreign direct investment.

© 2013 Blackwell Publishing Ltd.

HOME FIRM PERFORMANCE, FDI AND DIVESTITURES 9

when the sample is limited to exporters that start investing abroad. In this case, export turn-

over rises by up to 33.7 and 68.4 percentage points in the first and sixth year, respectively.9

The DiD measures show positive signs for employment and turnover growth in the short

and medium term. One reason for strong rise in turnover might be that foreign investments

TABLE 4Performance of High- and Low-technology Firms (D/DX-DI)

OutcomeVariable

xt + k–xt�1 TreatedFirms: HighTechnology

Diff-in-diff t-Value TreatedFirms: LowTechnology

Diff-in-diff t-Value

Exportturnover

t + 1 571 0.6749*** 3.663 1,384 0.3904*** 3.666t + 2 552 0.6030*** 3.205 1,342 0.5226*** 4.482t + 3 538 0.7641*** 3.613 1,321 0.5508*** 4.385t + 4 439 1.1824*** 4.584 1,118 0.6737*** 4.430t + 5 390 1.4059*** 4.577 1,012 0.4999*** 2.853t + 6 392 1.3694*** 4.267 997 0.6489*** 3.569

Exportshare

t + 1 570 0.0453*** 4.182 1,382 0.0112* 1.853t + 2 553 0.0427*** 3.759 1,342 0.0231*** 3.450t + 3 538 0.0510*** 4.040 1,321 0.0247*** 3.286t + 4 439 0.0896*** 5.694 1,116 0.0325*** 3.464t + 5 390 0.0952*** 5.449 1,014 0.0225** 2.105t + 6 392 0.0961*** 5.351 997 0.0296*** 2.649

Operatingturnover

t + 1 570 0.0956*** 3.256 1,382 0.0752*** 3.293t + 2 553 0.1188*** 3.277 1,342 0.0815*** 3.182t + 3 538 0.1681*** 3.724 1,321 0.0860** 2.565t + 4 439 0.2242*** 3.662 1,116 0.0869* 1.958t + 5 390 0.2643*** 3.414 1,014 0.1009* 1.905t + 6 392 0.2930*** 3.310 997 0.1361** 2.293

Employment t + 1 499 0.0361 1.224 1,213 0.0206 0.993t + 2 446 0.0664 1.610 1,082 0.0374 1.409t + 3 450 0.0130 0.321 1,087 0.0773*** 2.584t + 4 371 0.0700 1.217 947 0.0433 1.109t + 5 285 0.0639 0.914 747 0.0584 1.075t + 6 349 0.0543 0.794 883 0.0739 1.377

Labourproductivity

t + 1 498 0.0623** 2.160 1,211 0.0329 1.451t + 2 446 0.0635* 1.796 1,081 0.0102 0.442t + 3 449 0.1058*** 2.694 1,085 0.0163 0.622t + 4 371 0.0741 1.470 946 0.0317 0.920t + 5 285 0.0638 1.090 747 0.0742 1.556t + 6 349 0.1998*** 2.695 883 0.0823* 1.832

TFP t + 1 379 2.0443*** 5.624 944 �0.8965*** 3.680t + 2 338 2.3176*** 5.362 827 �1.0360*** 3.550t + 3 346 2.1302*** 5.311 841 �0.8549*** 3.062t + 4 292 2.5029*** 5.122 742 �0.9267*** 2.808t + 5 227 3.0165*** 4.435 606 �1.1440*** 2.733t + 6 268 3.0113*** 5.103 688 �1.2745*** 3.319

Notes:(i) Reported are the results for the difference-in-difference estimations with xt + k–xt�1, where t = change period andk takes the values 1–6. (ii) The t-values are reported and *p < 0.10, **p < 0.05, ***p < 0.01.

9 Results are available on request.

© 2013 Blackwell Publishing Ltd.

10 D. ENGEL AND V. PROCHER

based on cross-border mergers and acquisitions (M&As) increase the opportunity to exploit

economies of scale within the enlarged corporate network (e.g. R€oller et al., 2001). Moreover,

turnover growth is always higher than employment growth, and thus, labour productivity also

increases significantly. However, productivity effects are insignificant for the TFP measure.

Our results are generally in line with many recent empirical studies for Europe that find

positive home performance effects of firms investing abroad. In particular, taking a much lar-

ger set of firms from major industry and service sectors into account than most other studies,

we confirm findings of Barba Navaretti et al. (2010) for France. In addition, we provide

empirical evidence that output growth of treated firms is mainly driven by their export activ-

ity. As a robust check, we restricted our analysis to firms within each cohort (see Table 1)

that exhibit a complete post-change record (till t + 4) in the respective outcome variables.

The results in the restricted and unrestricted samples are similar.10

Examining the moderating role of industry affiliation, Table 4 depicts separate results for

firms in high-technology and in low-technology industries. While we do not have data about

expenditures for research and development, we apply the NIW/ISI list of high-tech industries

in manufacturing (Legler and Frietsch, 2007), and the list of high-tech service industries

suggested by Nerlinger (1998). Exporters in high-tech industries exhibit a stronger growth in

their export turnover and export share than non-treated firms in high-tech industries, whereas

companies in low-tech industries achieve a remarkable lower growth in these measures. For

example, firms in high-tech industries display a significant annual growth rate in the export

share of 4.5 up to 9.6 percentage points in the post-switching periods compared with exporters

that did not become engaged in FDI. In contrast, firms in low-tech industries attain an export

share growth of 1.1–2.96 percentage points only. The difference might arise due to a stronger

domestic centralisation as well as vertical specialisation of certain products for firms in high-

technology industries. In contrast, firms in low-technology industries opt more often for a sim-

ple replication of home production in foreign countries. This notable difference in the invest-

ment behaviour might explain why firms in high-technology industries achieve a significant

increase in labour and total factor productivity. Vertical specialisation and/or home centralisa-

tion of certain products allow to better exploit economies of scale. In sum, firms in high-

technology industries that become engaged in FDI clearly outperform non-switching firms as

well as switching firms in low-technology industries. Irrespective from any firm and industry-

specific differences, the major finding still holds – exporting and FDI are complements rather

than substitutes.

b. Foreign Divestitures

It remains an open question whether the complementarity between FDI and exporting is

also displayed in the opposite direction. Table 5 reports the DiD measures for MNEs that

divest all foreign operations to become either pure exporters or domestic firms which only

serve the home market. We find that complete foreign divestitures have no significant effect

on the export activity compared with non-treated MNEs. In fact, two-thirds of divesting firms

are engaged in exporting after the divestiture. These firms display a significant increase in

export activity in the first year after the drawback from abroad.11 In the medium and long

10 Results are available on request.11 Results are available on request.

© 2013 Blackwell Publishing Ltd.

HOME FIRM PERFORMANCE, FDI AND DIVESTITURES 11

term, however, these switching firms do not display a higher export activity than MNEs that

did not change. Obviously, home plants cannot gain from the strategic decision to shut down

foreign affiliates. Krautheim (2009) further argues that divesting might reduce in the long

term the chance to export home-centred products to foreign markets at lower costs.

Export turnover, operating revenue and employment are not significantly affected by

changing the internationalisation mode. Moreover, both productivity measures exhibit negative

coefficients which are, however, not significant at the conventional levels. Thus, a retreat from

international markets is neither linked to performance losses nor gains at home. Robustness

checks for firms with a complete post-change record confirm these results. This finding

TABLE 5The Effect of Foreign Divestment on Firm’s Home Performance (DI-DX/D)

Outcome Variable xt + k–xt�1 Treated Firms Diff-in-diff t-Value

Export turnover t + 1 665 �0.4963 0.472t + 2 614 �0.9825 0.478t + 3 606 �0.3736 0.253t + 4 523 �0.5092 0.287t + 5 411 �2.0466 0.582t + 6 392 �0.4682 0.189

Export share t + 1 665 �0.0260 0.406t + 2 644 �0.0369 0.391t + 3 634 �0.0202 0.249t + 4 522 �0.0174 0.168t + 5 465 �0.0649 0.382t + 6 454 �0.0193 0.129

Operating turnover t + 1 663 �0.4083 0.668t + 2 612 �0.3302 0.441t + 3 606 �0.3658 0.499t + 4 520 �0.4953 0.542t + 5 410 �0.5381 0.436t + 6 391 �0.6233 0.429

Employment t + 1 602 �0.2366 0.489t + 2 509 �0.3038 0.481t + 3 495 �0.2928 0.432t + 4 465 �0.2937 0.380t + 5 248 0.0237 0.032t + 6 339 �0.3371 0.282

Labour productivity t + 1 600 �0.1424 0.542t + 2 507 �0.0587 0.113t + 3 494 �0.1407 0.379t + 4 462 �0.1779 0.442t + 5 248 �0.0704 0.116t + 6 338 �0.1711 0.247

TFP t + 1 450 �0.3521 0.226t + 2 372 �0.4871 0.245t + 3 368 �0.5972 0.289t + 4 339 �0.6364 0.271t + 5 185 �0.4465 0.100t + 6 238 �0.8813 0.238

Notes:(i) Reported are the results for the difference-in-difference estimations with xt + k–xt�1, where t = change period andk takes the values 1–6. (ii) The t-values are reported and significance level is 10%.

© 2013 Blackwell Publishing Ltd.

12 D. ENGEL AND V. PROCHER

contradicts findings that divestitures are positively evaluated by financial markets due to posi-

tive cumulative abnormal returns after the announcement of a divestiture (e.g. Mathur et al.,

2006). Nevertheless, divestments can be part of a retrenchment scheme due to a lack of strate-

gic fit. A foreign affiliate might no longer be consistent with the corporate image and strategy.

Moreover, the management might have decided to restructure and refocus the existing

business.

TABLE 6Performance of High- and Low-technology Firms (DI-DX/D)

OutcomeVariable

xt + k–xt�1 TreatedFirms: HighTechnology

Diff-in-diff t-Value TreatedFirms: LowTechnology

Diff-in-diff t-Value

Exportturnover

t + 1 206 �0.4879 0.784 459 �0.5001 0.564t + 2 183 �1.1615 0.802 431 �0.9057 0.565t + 3 181 �0.1332 0.134 425 �0.4804 0.404t + 4 154 �0.3846 0.328 369 �0.5622 0.395t + 5 120 �2.5272 0.999 291 �1.8482 0.682t + 6 119 �0.8622 0.608 273 �0.2999 0.146

Exportshare

t + 1 204 �0.0186 0.472 459 �0.0293 0.550t + 2 182 �0.0283 0.434 430 �0.0407 0.544t + 3 180 0.0068 0.135 426 �0.0316 0.473t + 4 153 �0.0142 0.213 367 �0.0188 0.224t + 5 119 �0.0655 0.564 291 �0.0646 0.484t + 6 118 �0.0240 0.267 273 �0.0174 0.143

Operatingturnover

t + 1 204 �0.3193 0.737 459 �0.4479 0.950t + 2 182 �0.2140 0.376 430 �0.3803 0.680t + 3 180 �0.2019 0.369 426 �0.4371 0.792t + 4 153 �0.3758 0.534 367 �0.5452 0.803t + 5 119 �0.4551 0.473 291 �0.5721 0.627t + 6 118 �0.6698 0.609 273 �0.6042 0.555

Employment t + 1 194 �0.2565 0.776 408 �0.2272 0.600t + 2 153 �0.3849 0.836 356 �0.2699 0.561t + 3 155 �0.3018 0.639 340 �0.2888 0.548t + 4 138 �0.3372 0.568 327 �0.2755 0.479t + 5 64 �0.0456 0.075 184 0.0463 0.084t + 6 108 �0.4597 0.527 231 �0.2821 0.309

Labourproductivity

t + 1 192 �0.0862 0.499 408 �0.1690 0.800t + 2 152 0.0903 0.226 355 �0.1214 0.316t + 3 154 �0.0378 0.155 340 �0.1877 0.632t + 4 137 �0.0936 0.319 325 �0.2133 0.693t + 5 64 0.1108 0.244 184 �0.1368 0.299t + 6 107 �0.1396 0.270 231 �0.1878 0.359

TFP t + 1 140 �0.0653 0.071 310 �0.4819 0.372t + 2 103 �0.0634 0.050 269 �0.6493 0.412t + 3 110 �0.2793 0.222 258 �0.7356 0.434t + 4 94 �0.2751 0.176 245 �0.7756 0.419t + 5 45 0.1695 0.063 140 �0.6555 0.188t + 6 75 �0.5706 0.247 163 �1.0264 0.341

Notes:(i) Reported are the results for the difference-in-difference estimations with xt + k–xt�1, where t = change period andk takes the values 1–6. (ii) The t-values are reported and significance level is 10%.

© 2013 Blackwell Publishing Ltd.

HOME FIRM PERFORMANCE, FDI AND DIVESTITURES 13

All the findings remain unchanged when the sample is split with respect to the industry

affiliation and general technology level. We fail to detect any significant effect on outcome

variables listed in Table 6. The overall results for divesting firms show no substantial perfor-

mance differences with respect to technology differences. Therefore, analysing reasons for

divestiture as well as transaction forms (selling, closing or spinning-off a foreign business)

might be essential in future research to further enhance the relationship between investment,

divestiture and subsequent corporate performance.

5. CONCLUSION

This paper analyses the effects of investing or divesting abroad on domestic enterprise per-

formance in a French context. A propensity score matching combined with a DiD estimator is

applied to derive empirical findings.

We find a substantial rise in the export share for firms becoming engaged in outward

investments indicating that FDI and exports are complements rather than substitutes. This

might explain why the annual employment and turnover growth is up to 18 percentage points

larger in the post-change periods for new MNEs compared with non-investing firms. The

complementarity between FDI and exports is stronger for switching firms in high-tech indus-

tries than for switching firms in low-tech industries, which might indicate that high-tech firms

opt to a larger extent for home centralisation of certain products and/or vertical specialisation

than low-tech firms. From a policy perspective, the step of firms to internationalise is very

positive because of the steady and strong business development at home in subsequent years.

Apart from FDI, foreign divestitures are a central part of global business dynamics. There-

fore, our study provides an unique contribution to the question on how divesting from abroad

affects home enterprise’ performance. Interestingly, the impact of real economic effects in

terms of export turnover, operating revenue, employment and productivity are negligible in

post-divestiture periods. Based on our findings, one can conclude that the home country does

not need not to fear negative repercussions from firms reverting to domestic operations, but

neither can it gain from foreign divestitures.

REFERENCES

Amador, J. and S. Cabral (2009), ‘Vertical Specialization Across the World: A Relative Measure’, NorthAmerican Journal of Economics and Finance, 20, 3, 267–80.

Barba Navaretti, G. and D. Castellani (2008), ‘Investment Abroad and Performance at Home: Evidencefrom Italian Multinationals’, in S. Brakman and H. Garretse (eds.), Foreign Direct Investment and theMultinational Enterprise (Cambridge, MA: MIT Press), 199–224.

Barba Navaretti, G., D. Castellani and A. C. Disdier (2010), ‘How Does Investing in Cheap LabourCountries Affect Performance at Home? Firm-level Evidence from France and Italy’, OxfordEconomic Papers, 62, 234–60.

Becker, S. O. and M.-A. Muendler (2008), ‘The Effect of FDI on Job Security’, The B.E. Journal ofEconomic Analysis & Policy, 8, Article 8.

Benito, G. R. G. (1997), ‘Divestment of Foreign Production Operations’, Applied Economics, 29, 10,1365–78.

Bernard, A. B. and J. B. Jensen (1999), ‘Exceptional Exporter Performance: Cause, Effect, or Both?’Journal of International Economics, 47, 1, 1–25.

Bernard, A. B. and J. B. Jensen (2007), ‘Firm Structure, Multinationals, and Manufacturing PlantDeaths’, Review of Economics and Statistics, 89, 1, 1–11.

Blundell, R. and M. Costa Dias (2000), ‘Evaluation Methods for Non-experimental Data’, Fiscal Studies,21, 4, 427–68.

© 2013 Blackwell Publishing Ltd.

14 D. ENGEL AND V. PROCHER

Blundell, R. and M. Costa Dias (2002), ‘Alternative Approaches to Evaluation in EmpiricalMicroeconomics’, Portuguese Economic Journal, 1, 1, 1–38.

BvDEP. AMADEUS Database, Release 202, 168, 146, 136, 113 and 88 (Bureau van Dijk ElectronicPublishing, BvDEP). Available at: www.amadeus.bvdep.com (15 March 2012).

Cao, J., S. Owen and A. Yawson (2008), ‘Analysing the Wealth Effects of UK Divestitures: An Exami-nation of Domestic and International Sales’, Research in International Business and Finance, 22, 1,68–84.

Chaney, T. (2005), Liquidity Constrained Exporters. Mimeo (Chicago, IL: University of Chicago).Denis, D. K. and D. K. Shome (2005), ‘An Empirical Investigation of Corporate Asset Downsizing’,

Journal of Corporate Finance, 11, 3, 427–48.Desai, M. A., F. C. Foley and J. R. Hines (2009), ‘Domestic Effects of the Foreign Activities of US

Multinationals’, American Economic Journal. Economic Policy, 1, 1, 181–203.Evans, D. S. (1987), ‘The Relationship Between Firm Growth, Size, and Age: Estimates for 100 Manu-

facturing Industries’, Journal of Industrial Economics, 35, 2, 567–83.Greenaway, D., A. Guariglia and R. Kneller (2007), ‘Financial Factors and Exporting Decisions’,

Journal of International Economics, 73, 2, 377–95.Hanson, R. C. and M. H. Song (2003), ‘Long-term Performance of Divesting Firms and the Effect of

Managerial Ownership’, Journal of Economics and Finance, 27, 3, 321–36.Head, K. and J. Ries (2003), ‘Heterogeneity and the Foreign Direct Investment Versus Exports

Decision of Japanese Manufacturers’, Journal of the Japanese and International Economies, 17, 4,448–67.

Head, K. and J. Ries (2004), ‘Exporting and FDI as Alternative Strategies’, Oxford Review of EconomicPolicy, 20, 3, 409–23.

Heckman, J. J. (1978), ‘Dummy Endogenous Variables in a Simultaneous Equation System’, Econome-trica, 46, 4, 931–60.

Heckman, J. J., P. Ichimura and H. Todd (1998), ‘Matching as an Econometric Evaluation Estimator’,Review of Economic Studies, 65, 2, 261–94.

Heckman, J. J., R. J. LaLonde and J. A. Smith (1999), ‘The Economics and Econometrics of ActiveLabour Market Programs’, in A. Ashenfelter and D. Card (eds.), Handbook of Labour Economics(Amsterdam: Elsevier), Vol. 3A, 1866–2097.

Helpman, E., M. J. Melitz and S. R. Yeaple (2004), ‘Export Versus FDI with Heterogeneous Firms’,American Economic Review, 94, 1, 300–16.

Hering, L., T. Inui and S. Poncet (2010), ‘The Elusive Impact of Investing Abroad: Can an Analysis ofthe Motives for FDI Help?’, Working Paper 2010/12 (Florence: European University Institute).

Hijzen, A., T. Inui and Y. Todo (2007), ‘The Effects of Multinational Production on Domestic Perfor-mance: Evidence from Japanese Firms’, Discussion Paper Series 07-E-006 (Tokyo: Research Instituteof Economy, Trade and Industry).

INSEE – Institut national de la statistique et des �etudes �economiques (2012), ‘Principaux Resultats desEntreprises par Secteur en 2010’, Available at: http://www.insee.fr/fr/themes/tableau.asp?reg_id=0&ref_id=NATTEF09225 (15 March 2012).

J€ackle, R. and G. Wamser (2010), ‘Going Multinational: What are the Effects on Home Market Perfor-mance?’ German Economic Review, 11, 2, 188–207.

Jensen, M. C. (1986), ‘Agency Costs of Free Cash Flow, Corporate Finance and Takeovers’, AmericanEconomic Review, 76, 2, 323–29.

Kleinert, J. and F. Toubal (2007), ‘The Impact of Locating Production Abroad on Activities atHome: Evidence from German Firm-Level Data’, Discussion Paper 314 (Tubingen: University ofTubingen).

Krautheim, S. (2009), ‘Export-supporting FDI’, Working Paper, Economics Studies 20/2009 (Frankfurtam Main: Deutsche Bundesbank).

Lechner, M. (2001), ‘Identification and Estimation of Causal Effects of Multiple Treatments Under theConditional Independence Assumption’, in M. Lechner and F. Pfeiffer (eds.), Econometric Evaluationof Labour Market Policies (Heidelberg: Physica/Springer). 43–58.

Lee, D. and R. Madhavan (2010), ‘Divestiture and Firm Performance: A Meta-analysis’, Journal ofManagement, 36, 6, 1345–71.

Legler, H. and R. Frietsch (2007), ‘Neuabgrenzung der Wissenswirtschaft – forschungsintensiveIndustrien und wissensintensive Dienstleistungen (NIW/ISI-Listen 2006)’, in Bundesministerium fur

© 2013 Blackwell Publishing Ltd.

HOME FIRM PERFORMANCE, FDI AND DIVESTITURES 15

Bildung und Forschung (BMBF) (ed.), Studien zum deutschen Innovationssystem Nr. 22/2007(Hannover/Karlsruhe: NIW/Fraunhofer).

Leuven, E. and B. Sianesi (2003), ‘PSMATCH2: Stata Module to Perform Full Mahalanobis and Propen-sity Score Matching, Common Support Graphing, and Covariate Imbalance Testing’, Statistical Soft-ware Components, Boston College Department of Economics. This version: 3.1.4 17dec2008.

Levinsohn, J., A. Petrin and B. Poi (2003), ‘Production Function Estimation in Stata Using Inputs toControl for Unobservables’, Stata Journal, 4, 2, 113–23.

Markusen, J. (1995), ‘The Boundaries of the Multinational Enterprise and the Theory of InternationalTrade’, Journal of Economic Perspectives, 9, 2, 169–89.

Martins, P. S. and Y. Yang (2009), ‘The Impact of Exporting on Firm Productivity: A Meta-analysis ofthe Learning-by-exporting Hypothesis’, Review of World Economics, 145, 3, 431–45.

Mathur, I., K. C. Gleason and M. Singh (2006), ‘Foreign Asset Divestitures by U.S. firms: An Analysisof Motives and Valuation Consequences’, Available at SSRN: http://ssrn.com/abstract=891871(accessed 15 September 2009).

Nerlinger, E. (1998), ‘Standorte und Entwicklung junger innovativer Unternehmen: Empirische Ergeb-nisse fur West-Deutschland’, Dissertation University L€uneburg, ZEW Wirtschaftsanalysen, 27 (Baden-Baden: Nomos Verlag).

Roberts, M. J. and J. R. Tybout (1997), ‘The Decision to Export in Colombia: An Empirical Model ofEntry with Sunk Costs’, American Economic Review, 87, 4, 545–56.

R€oller, L.-H., J. Stennek and F. Verboven (2001), ‘Efficiency Gains from Mergers’, European Economy,5, 1, 31–128.

Roper, S., J. H. Love and D. A. Higon (2006), ‘The Determinants of Export Performance: Evidence forManufacturing Plants in Ireland and Northern Ireland’, Scottish Journal of Political Economy, 53, 5,586–615.

Rosenbaum, P. R. and D. B. Rubin (1983), ‘The Central Role of the Propensity Score in ObservationalStudies for Causal Effects’, Biometrika, 70, 1, 41–55.

Stiebale, J. (2010), ‘The Impact of Foreign Acquisitions on the Investors’ R&D Activities – Firm-LevelEvidence’, Ruhr Economic Papers No. 161 (Essen: RWI).

Stiebale, J. (2011), ‘Do Financial Constraints Matter for Foreign Market Entry? A Firm-Level Examina-tion’, The World Economy, 34, 1, 123–53.

Wagner, J. (2007), ‘Exports and Productivity: A Survey of the Evidence from Firm Level Data’,The World Economy, 30, 1, 60–82.

© 2013 Blackwell Publishing Ltd.

16 D. ENGEL AND V. PROCHER