This paper compares the performance of purely domestic plants, domestic exporters and domestic multinationals. For our empirical analysis we utilise a non-parametric approach based on the principle of first order stochastic dominance. We find that the distributions for multinationals dominate that of domestic exporters and non-exporters, while we do not find clear differences in plant performance between domestic exporters and non-exporters.exporting, FDI, multinationals, productivity, profitability, plant heterogeneity

Eric Strobl

Holger Görg

Sourafel Girma

English

Research Papers in Economics

 
 
 
 
 
 
 
Sourafel Girma, 
Holger Görg and  
Eric Strobl 
Exports, international investment, and 
plant performance:  
Evidence from a non-parametric test  
 
Discussion Papers 
Berlin, November 2003   
 
 
 
 
 
 
 
 
 
 
 
 
 
Opinions expressed in this paper are those of the author and do not necessarily reflect views 
of the Institute. 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
DIW Berlin 
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ISSN 1619-4535 
  
Exports, international investment, and plant performance:  
Evidence from a non-parametric test  
 
 
 
Sourafel Girma 
University of Leicester 
 
Holger Görg  
University of Nottingham and DIW Berlin 
 
Eric Strobl 
Université catholique de Louvain 
 
 
 
Abstract 
This paper compares the performance of purely domestic plants, domestic exporters and 
domestic multinationals.  For our empirical analysis we utilise a non-parametric approach 
based on the principle of first order stochastic dominance.  We find that the distributions for 
multinationals dominate that of domestic exporters and non-exporters, while we do not find 
clear differences in plant performance between domestic exporters and non-exporters. 
 
Keywords: exporting, FDI, multinationals, productivity, profitability, plant heterogeneity 
 
JEL classification: F23, F14, D21 
 
 
 
 
 
Acknowledgements: The authors are grateful to Forfás, in particular Marcus Breathnach, for the provision of the 
data.  Holger Görg gratefully acknowledges financial support through the Leverhulme Trust (Grant No. 
F114/BF).  Eric Strobl is grateful for a European Commission Marie Curie Fellowship.   1
Introduction 
The empirical findings of substantial heterogeneity in firm performance across 
exporters and non-exporters (e.g., Clerides et al., 1998, Bernard and Jensen, 1999, Wagner, 
2002) have spun off a number of recent theoretical papers, attempting to explain this plant or 
firm level heterogeneity in a formal setting.  Examples of such models are Melitz (2003) and 
Bernard et al. (2003), both of which allow for plant level heterogeneity in efficiency and find 
that in equilibrium more efficient firms select into exporting, while less efficient ones serve 
the local market only.   
In an extension of these models, Helpman et al. (2003) allow for three modi operandi 
for firms: serving only the domestic market, exporting, or investing abroad to sell on the 
foreign market (FDI).  They show that the most efficient firms will engage in FDI while the 
least efficient will operate only in the domestic market.  Firms with medium efficiency levels 
will become exporters, but not undertake FDI.  While this clear-cut prediction emerges from 
the theory, one may not expect it to hold in empirical data.  For example, due to uncertainty, 
firms may not immediately enter into exporting even if they have the necessary level of 
efficiency.   
We use plant level data to compare productivity and profitability measures across 
these three groups of establishments.  There has been little work in this area, as most micro 
level datasets do not allow, for a given home country, to distinguish between firms that only 
service the local market, firms that export, and firms that choose to invest abroad.
1  Our 
dataset provides information for manufacturing plants in the Republic of Ireland on all three 
                                                           
1 One recent study we are aware of that compares productivity for domestic firms and domestic multinationals is 
by Doms and Jensen (1998) for the US.  There has, however, been a multitude of studies comparing productivity   2
of these dimensions.  Moreover, in the comparison of the performance measures across the 
three firm types we do not just look at one part of the distribution, i.e., the mean, as is the case 
in most of the related literature cited above.  Rather, we test for differences in all moments of 
the distribution using a non-parametric approach based on the concept of first order stochastic 
dominance.
2   
Ireland serves as an interesting case study for a number of reasons.  Firstly, on 
average, almost 60 percent of domestic firms export and the average export intensity in 
manufacturing industries (averaged over exporters and non-exporters) is around one-third of 
output (Ruane and Sutherland, 2002).  Secondly, while the Irish industrial structure is 
significantly influenced by foreign multinationals, Irish outward FDI has recently also 
increased substantially (Görg, 2000).  Hence, we would expect a significant number of 
domestic exporters as well as domestic multinationals in the economy.  Thirdly, the Irish data 
set is one of a (to the best of our knowledge) limited number of comprehensive micro level 
surveys collecting information on exporting and outward investment at the plant level.   
Methodology 
For our analysis we invoke the concept of first order stochastic dominance which 
allows us to compare and rank the distributions of measures of plant performance.  Let F and 
G denote two cumulative distribution functions for two comparison groups, e.g., productivity 
of domestic multinationals and domestic exporters.  First-order stochastic dominance of F 
                                                                                                                                                                                     
in domestic firms and foreign-owned multinationals located in the host country, see, for example, Girma at al. 
(2001) for the UK, Doms and Jensen (1998) for the US and Globerman (1994) for Canada.   
2 See Delgado et al. (2002) for an application of this approach in their comparison of productivity between 
exporters and non-exporters.  The paper by Girma et al. (2003) is more closely related to our paper, also 
appealing to the Helpman et al. (2003) model.  However, their main comparison is between UK non-exporters, 
UK exporters and foreign multinationals, given the absence of information on UK multinationals in their dataset.  
They attempt to construct data on UK multinationals from other datasources, but this does not give them a   3
with respect to G is defined as  0 ) ( ) ( ≤ − z G z F  uniformly in ℜ ∈ z , with strict equality for 
some z.  Since this considers all moments of the distribution it is a stricter test of productivity 
differences than just comparing mean levels of productivity.  In the context of this paper these 
tests therefore encompass the possibility that establishments of the same productivity level 
may choose different forms of commerce, but restrict the test such that there must be 
statistically robust differences between the distributions.  That is, the degree of uncertainty in 
behaviour cannot be too large so that the structure of commerce and plant heterogeneity are 
no longer meaningfully related. 
In order to implement the comparison we follow Delgado et al. (2002) and adopt the 
nonparametric one-sided and two-sided Kolmogorov - Smirnov (KS) tests.
3  The two-sided 
KS statistic tests the hypothesis that both distributions are identical, and the null and 
alternative hypotheses can be expressed as:  
ℜ ∈ ∀ = − z z G z F H 0 ) ( ) ( : 0  vs.  0 ) ( ) ( : 1 ≠ − z G z F H  for some  ℜ ∈ z  (1) 
By contrast, the one-sided test of stochastic dominance can be formulated as : 
ℜ ∈ ∀ ≤ − z z G z F H 0 ) ( ) ( : 0  vs.  0 ) ( ) ( : 1 > − z G z F H  for some  ℜ ∈ z  (2) 
Hence, in order to conclude that F stochastically dominates G we need to reject the null 
hypothesis for the two sided test, but not reject the null for the one sided test.   
The KS test statistics for the two and one sided tests are, respectively  
{} ) ( ) ( max
.
1 2 i m i n N i z G z F
N
m n
KS − =
≤ ≤      (3) 
) ( ) ( max
.
1 1 i m i n N i z G z F
N
m n
KS − =
≤ ≤
     (4) 
                                                                                                                                                                                     
complete coverage of all UK MNEs.  In contrast, our dataset allows the identification of all domestic 
multinationals.  Furthermore, their data is company level, not plant level as in our analysis.   4
where  n and m are the sample sizes from the empirical distributions of F and G 
respectively, and N = n+m.   
Data 
Our data come from the Annual Business Survey of Economic Impact (ABSEI), an 
annual survey of a large sample of manufacturing plants in the Republic of Ireland.  Plants are 
included in this survey if they have at least 10 employees, but are not necessarily dropped if 
they fall below this threshold.  The coverage is about 60 to 80 per cent of the targeted 
population.  Data from the ABSEI are available for the year 2000.
4   
The data set provides plant level data on, inter alia, nationality of ownership, output, 
exports, employment and expenditure on labour and other inputs for Irish manufacturing 
plants.
5  What makes the data most interesting from our point of view is an indicator variable 
that is equal to one if a plant has “any overseas offices or distribution facilities”.  Taking all 
this information together, we can deduct from the data whether a domestic firm is a 
multinational, an exporter, or just a plant serving the local market, making our datasource 
quite unique in an international comparison.   
We calculate and compare three measures of establishment performance: (1) sales per 
employee, (2) value added per employee, and (3) net profit per employee.
6  The first two 
measures are essentially indicators of labour productivity, while the third measure provides an 
indicator of financial performance.  Value added is defined as sales minus intermediate input 
purchases, while net profits are value added minus labour cost and other expenditure.  All 
                                                                                                                                                                                     
3 See, for example, Conover (1999) for a discussion. 
4 Strictly speaking, the ABSEI also includes information for 1999 but this is included in the 2000 survey via 
retrospective questions. 
5 Forfás defines a plant as foreign owned if 50 percent or more of its shares are held by foreign owners.     5
three performance indicators are calculated relative to the two-digit industry mean to ensure 
transitivity among comparisons and are in logged values.
7   
Results 
In what follows below, we label domestic non-exporters DN, domestic exporters DE 
and domestic multinationals MN.  Table 1 provides some summary statistics on the three 
performance measures for the three groups of firms separately.  It is clear that the means for 
MN are higher than the means for either DE or DN for all three measures of plant 
performance.  However, note that the standard deviations for MN are also highest, thus 
suggesting that the largest heterogeneity in plant performance is among domestic 
multinationals.  From the simple means it is not obvious that domestic exporters outperform 
domestic non-exporters.   
[Table 1 here] 
These summary statistics, of course, only look at two moments of the performance 
measure distribution, namely the mean and standard deviation. A simple preliminary manner 
of examining differences of the entire distribution of the performance measures is to plot 
cumulative distribution functions (cdf) and compare these across the three groups of 
establishments.  We do this here for the value added measure only in Figures 1 through 3, but 
emphasize that similar visual difference across the three groups were also observed for the 
other two measures.
8  Accordingly, while there appear to be no differences in the cumulative 
                                                                                                                                                                                     
6 One should note that we cannot calculate total factor productivity since there is no reliable estimate of capital 
stock at the plant level available in the data. 
7 This also helps to mitigate concerns that performance differences simply reflect differences in the sectoral 
composition of the three firm types.   
8 Detailed results are available from the authors.   6
distribution between DN and DE plants, that of MN plants lies clearly to right of these two 
groups. 
In order to test specifically for differences in all moments of the distribution we 
calculate the above described KS tests of first order stochastic dominance, the results of 
which for all three measures are reported in Table 2.  These show that we cannot reject the 
hypothesis of identical distributions of all three performance measures for exporters relative 
to non-exporters.  Thus, these results for the Irish case are not fully in line with the previous 
empirical literature (e.g., Clerides et al., 1998, Bernard and Jensen, 1999, Wagner, 2002), 
which finds substantial differences in productivity between exporters and non-exporters.   
The comparisons of Irish MNEs with exporters or non-exporters are, by contrast, in 
line with the predictions of the Helpman et al. (2003) model.  Specifically, the KS test 
statistics in Table 2 suggest that the distributions of both measures of labour productivity and 
profits per employee of multinationals stochastically dominate those of both non-exporters 
and exporters.  Hence, we find statistically significant productivity differences between 
domestic multinationals and both domestic exporters and non-exporters.   
[Table 2 and Figures 1-3 here] 
Conclusions 
This paper compares labour productivity and profitability differences across purely 
domestic plants, domestic exporters and domestic multinationals in Ireland.  Thus, our paper 
provides empirical evidence closely related to a number of recent theoretical papers dealing 
with heterogeneity at the plant level across these three types of establishments.  For our 
empirical analysis we utilise a non-parametric approach based on the principle of first order 
stochastic dominance.  Comparing the cumulative distributions of the measures of plant   7
performance across the three types of plants we find that the distributions for multinationals 
dominate that of domestic exporters and non-exporters, while we do not find clear differences 
in plant performance between domestic exporters and non-exporters.  The result that 
multinationals dominate the other two groups of plants is in line with the theoretical model by 
Helpman et al. (2003).     8
References 
Bernard A.B., Eaton J., Jensen B. and S.S. Kortum (2003), “Plants and productivity in 
international trade, American Economic Review, Vol. 93, pp. 1268-1290. 
Bernard, A.B. and Jensen, J.B. (1999), “Exceptional exporter performance: Cause, effect, or 
both?”, Journal of International Economics 47, 1-25. 
Clerides, S., Lach, S. and Tybout, J. (1998), “Is learning by exporting important? Micro-
dynamic evidence from Columbia, Mexico and Morocco”, Quarterly Journal of Economics 
113, 903-948. 
Conover W. J. (1999), Practical Nonparametric Statistics, John Wiley & Sons. 
Delgado, M. A., Farinas, J. C., and S. Ruano (2001), "Firm productivity and export markets: 
A non-parametric approach", Journal of International Economics 57(2), 397-422. 
Doms, M.E. and J.B. Jensen (1998), “Comparing wages, skills, and productivity between 
domestically and foreign-owned manufacturing establishments in the United States”, in R. 
Baldwin, R. Lipsey and J.D. Richardson (eds.), Geography and Ownership as Bases for 
Economic Accounting, Chicago: Chicago University Press, 235-255. 
Girma, S., D. Greenaway and K. Wakelin (2001), "Who benefits from Foreign Direct 
Investment in the UK?", Scottish Journal of Political Economy 48, 119-133. 
Girma, S., R. Kneller and M. Pisu (2003), “Exports versus FDI: An empirical test”, mimeo, 
University of Nottingham. 
Globerman, S., J.C. Ries and I. Vertinsky (1994), “The economic performance of foreign 
affiliates in Canada”, Canadian Journal of Economics 27, 143-156. 
Görg, H. (2000): “Irish Outward Investment in the US: Evidence and Further Issues”, Journal 
of the Statistical and Social Inquiry Society of Ireland 30, 33-52. 
Helpman E., Melitz M.J., and S.R. Yeaple (2003), “Export versus FDI with heterogeneous 
firms”, American Economic Review, forthcoming. 
Melitz M.J. (2003), “The impact of trade on intra-industry reallocations and aggregate 
industry productivity, Econometrica, forthcoming. 
Ruane, F. and J. Sutherland (2002), “Globalization, Europeanization and Trade in the 1990s: 
Export Responses of Foreign and Indigenous Manufacturing Companies”, Trinity Economic 
Paper 02/04, Trinity College Dublin. 
Wagner, J. (2002), “The causal effects of exports on firm size and labor productivity: First 
evidence from a matching approach”, Economics Letters 77, 287-292. 
   9
 
Table 1: Means and standard deviations for DN, DE and MN 
 
DN DE MN 
Absolute values     
sales/employee 87.837  96.493  122.397 
80.191 101.166  131.755 
value added / employee  66.580  74.418  94.797 
74.008 89.866  121.807 
profits / employee  33.320  32.370  43.199 
41.715 57.991 77.100 
log value relative to industry mean   
sales/employee 0.895  0.955  1.249 
0.688 0.700 1.258 
value added / employee  0.872  0.949  1.295 
0.814 0.827 1.663 
profits / employee  0.969  0.943  1.188 
0.888 0.887 1.626 
   10
 
Table 2: Kolmogorov-Smirnov tests for comparison of DN, DE and MN 
 
Panel A: log (sales / employee) 
 
F vs G  F=G  F≤G G≤F 
DE vs DN  0.0797 
(0.142) 
0.0797 
(0.071) 
-0.0279 
(0.723) 
MN vs DN  0.2430** 
(0.000) 
0.2430*** 
(0.000) 
0.0000 
(1.000) 
MN vs DE  0.1855** 
(0.000) 
0.1855** 
(0.000) 
0.0000 
(0.100) 
 
Panel B: log (value added / employee) 
 
F vs G  F=G  F≤G G≤F 
DE vs DN  0.0612 
(0.417) 
0.0367 
(0.570) 
-0.0612 
(0.211) 
MN vs DN  0.1373* 
(0.012) 
0.1373** 
(0.006) 
-0.0105 
(0.970) 
MN vs DE  0.1305** 
(0.005) 
0.1305** 
(0.002) 
-0.0037 
(0.995) 
 
Panel C: log (profit/employee) 
 
F vs G  F=G  F≤G G≤F 
DE vs DN  0.0767 
(0.172) 
0.0843 
(0.086) 
-0.0147 
(0.914) 
MN vs DN  0.2124** 
(0.000) 
0.2124** 
(0.000) 
-0.0081 
(0.982) 
MN vs DE  0.1678** 
(0.000) 
0.1678** 
(0.000) 
-0.0103 
(0.963) 
 
Notes: 
number of observations: DN: 307; DE 647; MNE 246 
p-values in parentheses 
* Significant at 10%, ** significant at 5%, *** significant at 1% confidence interval 
   11
 
Figure 1: VAD/Employee Level Differences between DN and DE 
 
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0.8
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-6.6 -5.6 -4.6 -3.6 -2.6 -1.6 -0.6 0.4 1.4
log(VAD/Employee)
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Figure 2: VAD/Employee Level Differences between DN and MN 
 
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   12
 
Figure 3: VAD/Employee Level Differences between DE and MN 
 
0
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Comparing wages, skills, and productivity between domestically and foreign-owned manufacturing establishments in the United States”,

Exceptional exporter performance: Cause, effect, or both?”,

Export versus FDI with heterogeneous firms”,

Exports versus FDI: An empirical test”, mimeo,

Firm productivity and export markets: A non-parametric approach&quot;,

Globalization, Europeanization and Trade in the 1990s: Export Responses of Foreign and Indigenous Manufacturing Companies”, Trinity Economic Paper 02/04,

Irish Outward Investment in the US: Evidence and Further Issues”,

Is learning by exporting important? Microdynamic evidence from Columbia, Mexico and Morocco”,

Plants and productivity in international trade,

Practical Nonparametric Statistics,

The causal effects of exports on firm size and labor productivity: First evidence from a matching approach”,

The economic performance of foreign affiliates in Canada”,

The impact of trade on intra-industry reallocations and aggregate industry productivity,

Who benefits from Foreign Direct Investment in the UK?&quot;,

Exports, International Investment, and Plant Performance: Evidence from a Non-Parametric Test

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Exports, International Investment, and Plant Performance: Evidence from a Non-Parametric Test

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