Exporting and profitability evidence for different firm sizes
PRELIMINARY VERSION - PLEASE DO NOT CITE
Saara Tamminen
∗
Marcel van den Berg
†
August 16, 2013
Abstract
Compiling two parallel data sets covering Dutch firms over the years
2002-2010 and Finnish firms over the years 2005-2010, we investigate
the relationship between trade status, firm size and profitability, employing four different profit measures. Results from regression analysis
suggest that internationalization of firm activities is not heavily correlated with profitability. We find largely insignificant or significantly
negative trade premia of small magnitude, which aligns with earlier research. In addition, the negative trade premia seem to be tied mainly
to exporting rather than to importing and particularly to micro and
small firms. Results from propensity score matching analysis show
little evidence supporting the hypothesis that exporting fosters profitability. Only for the Netherlands do we find some evidence suggesting
that export starters in manufacturing sectors materialize higher profits
in the longer run. The results indicate that new exporters seem to be
willing to fully explore the possibilities that foreign markets provide
even at the cost of (temporarily) materializing lower profits.
∗
Government Institute of Economic Research (VATT), Helsinki, Finland and Utrecht University School
of Economics, Utrecht, the Netherlands, e-mail: [email protected]
†
Utrecht University School of Economics, Utrecht, the Netherlands, e-mail: [email protected]
This study is funded by the Ministry of Economic Affairs and the Ministry of Foreign Affairs of the
Netherlands. We are grateful to Statistics Netherlands for providing us with the data underlying the
analysis. We thank Marjolijn Jaarsma for her invaluable support in our comprehension of the various data
sets. We also thank Charles van Marrewijk, Peter van Bergeijk, Martin Luppes and participants at VATT
Seminar for valuable feedback and comments. Any remaining errors are our own.
1
1
Introduction
The assumption of profit maximization is at the heart of economic theory
regarding firm behavior. While the notion that internationally competing
firms are on average more productive than domestically competing firms
is well-demonstrated (Wagner, 2011b), the evidence regarding the question
whether this productive advantage translates into higher profitability is less
conclusive (Wagner, 2011a). Theoretical models regarding the behavior of
individual firms on international markets are generally developed from the
notion that a firm starts exporting if expected profits derived from international markets at least equal the profits derived from only serving domestic
markets (Clerides, Lach, and Tybout, 1998; Melitz, 2003; Helpman, Itskhoki,
and Redding, 2010). However, the cost level of internationally competing
firms is generally higher than that of firms focusing on domestic markets. In
order to start exporting a firm faces additional fixed costs associated with
e.g. market research, locating foreign trade partners or modifying products
to comply with local regulations. In addition, internationally operating firms
generally have a higher skilled and more productive workforce, which requires
paying higher wages compared to domestically operating firms (ibid). The
combination of higher revenues associated with access to a larger market and
higher costs renders the net effect on firm-level profitability ambiguous.
The lack of empirical studies of the relationship between profitability and
internationalization of firm activities generally seems to stem from data limitations. However, the question on whether exporting affects firm level profitability is important. Financial analysts generally evaluate firm performance
based on information provided in financial statements whereby profitability
indicators play a particularly important role (Robinson, van Greuning, Henry,
and Broihahn, 2012). This implies that information regarding firm profitability is crucial in the decision making process of investors and thus affects the
availability of funds to the firm. Illustrative is the finding of Bridges and
Guariglia (2008) that higher profitability has a significantly negative effect
on the probability of bankruptcy. Productivity is correlated with profitability, but various other factors affect profitability as well. Therefore, we cannot
unconditionally extend the findings of the huge empirical literature regarding the relationship between productivity and internationalization to include
profitability.
In this study we aim to add to the still small literature dealing with the
relationship between profitability and internationalization. In doing so, we
pay particular between differences between firms from different size classes
and we distinguish between key sectors such as manufacturing, wholesale &
retail trading and services. Most micro data based studies regarding firm
2
heterogeneity focus on manufacturing sectors, mainly motivated by a lack of
data regarding trade in services. We contribute to the tiny literature dealing
with firm heterogeneity and trade in services employing Finnish micro data.
In addition, we employ four different profit measures to gain on understanding
of the robustness of our findings to the choice for a particular profit measure.
We employ gross profit margin, net profit margin, return on assets (ROA)
and gross profits per employee as profitability measures. Furthermore, we
add to the relatively small literature regarding profitability and exporting
among micro-sized and small firms, which are frequently neglected in the
heterogeneity literature, by separating for different firm size classes in our
analysis. Finally, to be able to assess the consistency and the robustness
of our findings we apply our empirical framework separately to firm level
micro databases from two small, open Western-European economies, namely
Finland and the Netherlands. We believe, as Hamermesh (2000, p. 376), puts
it, that ”the credibility of a new finding that is based on carefully analyzing
two data sets is far more than twice that of a result based only on one”.
This paper is organized as follows. Section 2 provides a brief discussion of
the existing empirical literature regarding the relationship between exporting and profitability. Section 3 introduces the Finnish and Dutch data sets
employed in the analysis. In section 4 we discuss the measurement of profitability and the methodology adopted in the empirical analysis. In section
5 we present our empirical findings. Section 6 concludes and provides some
directions for further research.
2
Literature
In recent years a few empirical studies dealing with profitability and internationalization have been added to the firm heterogeneity literature.1 The
topic has been studied more intensively in the international business literature. However, the available evidence is rather diffuse and fragmented in
terms of profit measures and research methodologies employed. Overall, the
relationship between internationalization and profitability is still not wellestablished and contradictory results are not uncommon.
Girma, Görg, and Strobl (2004), employing a series of Kolmogorov-Smirnov
tests, find no significant difference between domestic non-exporters and domestic exporters on the profit level per employee. Grazzi (2011) finds no significant relationship between exporting and profitability in Italy, just as do
Temouri, Vogel, and Wagner (2013) for British service exporters and Wagner
(2011a) for Germany. Illustrative for the lack of consensus, Temouri, Vogel,
1
see Wagner (2012) for a review.
3
and Wagner (2013) find a positive relationship between service exporting and
profitability in France and a negative relationship in Germany. In addition,
Fryges and Wagner (2010) document a small exporter premium on profit
margins for German manufacturing firms. They show that being an exporter
as such does not increase profits, and present evidence suggesting an inverted
U-shaped correlation between the export share and profits. For firms with
a sufficiently small share of exports in total sales they even find a negative
export premium. Kox and Rojas-Romagosa (2010) present evidence for the
Netherlands indicating that profitability in exporting firms is higher and that
more profitable firms seem to self-select into exporting. 2
In the field of international business management the relationship between internationalization and firm performance has been heavily debated
over the past decennia. For example, recent anecdotal evidence concerning
12 high-tech ’born global’ firms shows that the main reasons for these firms to
internationalize immediately after start-up relate more to market characteristics and market structure, than to financial motivations or expected excess
profits compared to starting locally (Kudina, Yip, and Barkema (2008)).
However, Bausch and Krist (2007, p 320) summarize the current state of affairs in this field of research in a series of citations as: ”inconsistent”, ”mixed”,
”decidedly mixed”, ”contradictory”, ”inconsistent and contradictory”, ”inconclusive and contradictory”, and ”conflicting”. Reviewing 43 empirical papers,
Sousa (2004) corroborates this conclusion arguing that little consensus has
been reached in the field, which has produced contradictory and fragmented
findings thus far. Nonetheless, in their meta-analysis of 36 studies from 25
years of research, Bausch and Krist (2007) present empirical evidence suggesting that internationalization does indeed foster firm performance, albeit
that this relationship is heavily moderated by various other firm characteristics, such as firm size and age. However, an important objection against
the way in which the relationship between exporting and firm performance is
generally analyzed in the field of international business management is that
it does not relate the performance of exporters to that of domestically oriented firms. This makes it difficult to claim that exporting in itself does or
does not foster firm performance, since a benchmark against which the performance of exporters is evaluated is lacking. Furthermore, many studies are
based on relatively small samples, which, combined with employing myriads
of methodologies and measures of internationalization and profitability, renders aggregating findings to the macro-economic level virtually impossible.
2
This paper does not mark an attempt to replicate the results presented by Kox and
Rojas-Romagosa (2010) for the Netherlands, since the aim of our paper is different, our
panel data set is compiled from alternative sources, the years covered by our panel data
are largely non-overlapping and we employ different profit measures.
4
The main lesson we learn from the preceding discussion is that no consensus has been reached thus far regarding the question whether internationalization fosters firm performance. That is, neither in the field of economics
and international trade, nor in the field of international business management
has this question been decidedly answered.
3
Data
For the empirical analysis we employ firm-level micro-data from Finland and
the Netherlands. In order to gain an understanding of the consistency and
robustness of our findings we run the analysis separately for both countries.
The main aim of the data preparation process is to maximize the comparability of the Finnish and the Dutch data for the analysis, particularly regarding
the profit concepts employed.
3.1
Finland
For the Finnish analysis we use tax data that includes firms operating in
all sectors. The database is described in detail in Tamminen and Chang
(2012, 2013). This study analyzes Finnish data from 2005 until 2010. The
data includes information regarding the export status of firms at each year
and detailed financial accounts and balance sheet information. Firms are
classified into four size categories according to the official EU-classification.3
Micro-sized companies are included in the analysis, except for companies
with less than 4 employees.
In addition to the main database, value added tax (VAT) records are
used for the identification of goods and services exporters and goods importers. The procedure for the identification of each firms exporting status
is explained in detail in Tamminen and Chang (2012). The database also allows the identification of multinational firms. The firms are grouped into 70
sectors, which correspond roughly to a combination of NACE 2 and 3-digit
classifications. Exporters identification is possible only in selected services
sectors. Companies belonging to other services sectors are not included in
the analysis. Since services and manufacturing exporters have typically significantly different types of production processes, manufacturing sectors and
3
Firms are classified into four groups: micro (less than 10 employees), small (10-49 employees), medium (50-249 employees), and large (at least 250 employees) firms according to
the definitions of European Union ( see http://ec.europa.eu/enterprise/policies/sme/factsfigures-analysis/sme-definition/).
5
services sectors are considered separately. Multinational firms can be identified from the legal form of the firm and from the information on foreign
subsidiaries. The analysis excludes self-employed and other firms with less
than 4 employees. Finnish tax legislation provides an incentive for owners of
small firms to artificially lower the pre-tax profits of the firm by withholding
part of the profits in the form of their wage. This renders the profit information of small firms difficult to compare with larger firms. After merging of
the two main databases, we obtain an unbalanced panel database of 122,621
observations (excluding outliers) from 34,941 firms for the period 2005-2010.
3.2
The Netherlands
For the empirical analysis we merge data from three main Dutch data sources:
(i) the General Business Register (GBR), (ii) the Baseline Database and (iii)
the International Trade Database, all provided by Statistics Netherlands into
a panel data set covering the years 2002 to 2010.4
The GBR is, in principle, exhaustive in the sense that it contains information about every firm in the Netherlands, including a set of basic firm
characteristics such as the number of employees in fulltime equivalents and
the sector in which the firm operates according to the internationally standardized ISIC Rev. 3.1 sector classification5 . We take from a separate but
related database information concerning the ultimate controlling institution
of the firm, indicating whether the ultimate controlling owner of the Dutch
firm is located abroad. The Baseline database contains a wealth of financial information collected from both corporate tax declarations and income
tax declarations of entrepreneurs, which is merged to the GBR. The Baseline database contains information about profits, gross output, value added
and the value of capital, labor and intermediate inputs. Because of their
fundamentally different nature, we separate the data into two main sectors,
manufacturing, and wholesale & retail trading sectors.6
4
We confine ourselves to discussing some key characteristics of each data source in this
paper. For details regarding the merging procedure see Van den Berg (2013).
5
The ISIC Rev. 3.1 sector classification equals the SBI’93 2 digit classification employed
by Statistics Netherlands
6
We focus the analysis of Dutch firms on manufacturing and wholesale & retail trading, thereby excluding service sectors, since data regarding trade in services are not yet
sufficiently available for the Netherlands. We choose financial intermediation as the cutoff point for service sectors, which corresponds to ISIC Rev. 3.1 section J, division 65.
Manufacturing sectors correspond in the analysis to ISIC Rev. 3.1 sections A through
I, excluding G. Wholesale & retail traders correspond to ISIC Rev. 3.1 section G. The
OECD and Eurostat recommend to define manufacturing as sections A through F and
to include section G to Q in services. However, in terms of goods trade this division is
6
Trade data are taken from the International Trade database and includes
information on all imports and exports of goods by Dutch firms. ExtraEU trade is recorded by the Customs Authority and intra-EU imports and
exports are recorded by the Dutch Tax Authority. The trade data available
at the firm level covers more than 80% of annual aggregate trade in terms of
value in the Netherlands.7 The merging procedure results in an unbalanced
panel data set containing a total of 501,769 observations of 139,160 firms
spanning a period of nine years (2002-2010).8
4
4.1
Methodology
Measuring profitability
The definition of profit (π) per employee (E ) is presented in equation 1
and shows that the profit level results from two factors: a scale effect (R,
accounting for annual revenue) and a margin effect ( Rπ ). The scale effect
refers to the level of revenue and the margin to the cost structure, i.e. to
the margin of profits over revenues. Gross profit per employee is calculated
according to the following equation, where the definition of gross profit is
derived in equation 2:
R ∗ ( πRG )
πG
=
(1)
E
E
Investors typically employ indicators based on margins and returns from
financial statements to assess the profitability and attractiveness of a firm as
an investment (Robinson, van Greuning, Henry, and Broihahn, 2012). A few
of the most common indicators for profitability in financial analysis based on
the International Financial Reporting Standards (IFRS) include (but are not
limited to):
Gross profit margin,
R−VC
VC
πG
=
=1−(
)
R
R
R
(2)
less sensible, since a considerable part of goods trade takes place in trade and transport
sectors it is therefore more appropriate to separate these sections from typical (financial
and public) service sectors.
7
The trade data are recorded on VAT-numbers. Connection to the firm identification
key used by Statistics Netherlands leads to a merging loss of about 20% of annual trade
values.
8
This is after eliminating four sectors with eight observations or less, micro firms (less
than four fulltime equivalents) and implausible observations with zero or negative output
or exports exceeding gross output.
7
Net profit margin,
πN
R − V C − F C − F CX
VC
FC
F CX
=
=1−(
)−(
)−(
)
R
R
R
R
R
(3)
and return on assets (ROA).
ROA = (
R
VC
FC
F CX
R − V C − F C − F CX
)=( )−(
)−(
)−(
)
A
A
A
A
A
(4)
R accounts for annual revenue (or sales), VC accounts for variable costs (or
costs of goods sold), FC are fixed costs of production that do not depend
on the size of production in the short run, F CX represents the fixed cost of
exporting (which is zero for companies operating only on the domestic market), and A represents total asset value. In addition, the operating margin
(return on sales) and return on equity are well-established profitability indicators in financial analysis (Robinson, van Greuning, Henry, and Broihahn,
2012). Investors typically use indicators defined per dividend or per share,
but most of the commonly available financial statements and balance sheets
do not include that information. Therefore, we restrict our analysis to the
four profitability indicators (equations 1, 2, 3 and 4) discussed above.
4.2
Empirical methodology
We start the empirical analysis by investigating the correlation between export status and profitability with basic pooled ordinary least squares (OLS)
regressions and fixed effects panel regressions. The existing empirical evidence suggesting that highly productive firms self-select into exporting is
compelling (Wagner, 2012). This implies that there is the threat of endogeneity arising in any OLS-regression of profitability on export status, due
to a sample selection bias. The purpose of the regressions in the first stage
is thus only to provide us an indication of the correlation between export
status and the various profitability measures we employ.
The pooled OLS-regressions are of the following form:
πXijt πXijt
0
0
or
= α + Yijt β + Zijt γ + ijt ,
Rijt
Aijt
π
(5)
where RXijt
refers to profit margin πX of firm i ∈ I from sector j ∈ J in
ijt
year t ∈ T relative to the mean profit margin over sales in sector j. Analoπ
gously, AXijt
represents the firms return on assets relative to the sector mean.
ijt
Yijt refers to a set of firm specific explanatory variables that include a set of
dummy variables indicating the trade status of the firm and a set of control
8
variables. The control variables included are the export share in total sales,
(the log of) firm size in terms of employment, a dummy variable indicating
whether the firm is under foreign control and (the log of) labor productivity
(defined as value added per employee). Non-trading firms mark the reference
group, implying that α captures the general correlation of being a non-trader
with the different profit measures. Albuquerque (2009) argues that size and
industry specific groups provide the best view on the comparative performance of firms, since business cycles are mostly industry specific and firm
size significantly affects the firms ability to respond to shocks. Therefore, a
full set of industry and year specific dummy variables, represented by Zijt ,
has been included in the regressions. Finally, the error term is denoted .
Since firm specific factors, such as the quality of management, are expected to affect both the decision to export and profitability of the firm, we
continue the analysis with fixed effect panel regressions, represented by the
following empirical model:
πXijt πXijt
0
0
or
= α + Yijt β + Zijt γ + µi + ijt ,
Rijt
Aijt
(6)
Each variable is defined in the same way as in equation 5. In addition, µi
represents the firm specific fixed effect.
Due to the expected sample selection bias, it is difficult to identify a
fully exogenous instrument for export status. To deal with this problem, and
in line with existing literature (Greenaway and Kneller, 2007), we employ
propensity score matching (PSM) to investigate the causality between export
status and the various profitability measures. The objective of this procedure
is to construct the non-observed counterfactual by matching each export
starter (a ’treated’ firm) to a firm from the control group (continuing nontrader, an ’untreated’ firm) based on similarity of firm characteristics before
the treatment. In this particular application the treatment is the export start
of the firm. This procedure enables us to evaluate whether export starters
convert to a different profitability growth path compared to continuing nontraders. Matching is done based on the estimated probability of becoming
an exporter. This probability is estimated by means of a probit-model of the
export status on a set of firm characteristics prior to export start (equation
7).
0
0
P r(exp = 1) = α + Yijt β + Zijt γ + ijt ,
(7)
The predicted values from this regression serve as the propensity score, based
on which export starters and continuing non-exporters are paired up for the
next step. The explanatory variables included in the probit-model are the
import status, a dummy variable indicating whether the firm is under foreign
9
control, the relative net profit margin, (the log of) labor productivity, labor
productivity growth, (the log of) assets per employee, (the log of) wages per
employee and two sets of dummy variables representing size class and sector.
All explanatory variables are lagged one year, in order to pair treated and
untreated firms based on the similarity of their characteristics one year prior
to treatment.
Firms from the export-starting cohort are then matched to a peer from
the continuingly non-exporting control group by minimizing the difference in
individual propensity scores; this procedure is referred to as nearest neighbor
propensity score matching. In addition, we force matching only to be allowed
between firms from the same sector. The only additional condition that needs
to be satisfied is that both treated and matched untreated firms continuously
stay in business throughout the period under investigation. In the final step
the profitability growth paths of the matched pairs of export starters and
continuing non-exporters are compared.
We define a firm as an export starter in case it reports exports larger
than zero in year t and export values of zero in t-1 and t-2 (see table 22
in the appendix for the exact definition of the various cohorts that serve as
input for the PSM-analysis). Firms that remain non-exporting for the full
three years represent the control group. The proposed variable selection and
methodology resemble the procedure presented by Ilmakunnas and Nurmi
(2010) and Arnold and Hussinger (2005) who find that particularly firm size,
productivity, labor quality, the price-cost margin and foreign ownership status affect the decision to export. As the data do not contain information on
the skill level of the employees, we use the logarithm of the wage bill over
employment as a proxy. Since an export start is expected to imply incurring
additional export related fixed costs, the lagged net profit margin relative to
the sector mean is included in the probit-regressions to account for differences in cost structures. The probit-regressions are run separately for each
combined cohort of export starters and continuing non-exporters.9
5
Empirical findings
The results presented in this section are based on separate analysis of the
compiled data sets concerning Finland and the Netherlands. Table 1 provides
an insight in the panel size of both countries. The table shows that the
available number of observations is larger for the Netherlands. This can be
9
The estimated propensities of becoming an exporter in Finland are remarkably similar
to the findings of Ilmakunnas and Nurmi (2010) when we align our data set with theirs
and limit the sample to firms with a minimum size of 20 employees.
10
explained by the relative size of both economies and the fact that the panel
regarding the Netherlands includes three more years. The table also shows
that exporting is more persistent among Finnish firms in every size class,
which is partly explained by the fact that the Finnish data also includes
services trade, whereas the Dutch data contains only goods trade.
Table 1: Persistence of exporting
firm size class
(fte)
Finland: goods and service trade
manufacturing
no. of observations
share exporting (%)
services
no. of observations
share exporting (%)
Netherlands: goods trade
manufacturing
no. of observations
share exporting (%)
wholesale & retail trade no. of observations
share exporting (%)
5.1
0-3
micro
4-9
small
10-49
medium large
50-249 ≥ 250
all
firms
excluded
excluded
excluded
excluded
24,278
31.4
32,022
24.6
25,402
52.5
23,687
37.4
6,680
84.1
5,429
43.8
1,602
93.5
1,566
51.2
57,962
48.4
62,704
31.7
excluded 149,983 111,976
excluded
13.2
26.0
excluded 143,968 70,759
excluded
28.9
46.4
14,276
51.0
7,405
61.0
1,384
71.1
728
79.4
277,619
20.6
222,860
35.7
Regression results
The pooled OLS-regressions are indicative for the degree of the correlation
between exporting and profitability. Tables 14 through 21 in the appendix
present the results of these regressions for both Finland and the Netherlands
and each of the four profitability measures employed. The results indicate
that the choice of profit measure does not heavily affect the findings. The
pooled OLS regressions show persistently that productivity and firm size are
the main determinants of profitability, with the former being positively associated with profits and the latter negatively. The results regarding the trade
status dummy variables are mixed, although we only find insignificant or
significantly negative coefficients, with the sole exception of two way traders
generating higher gross profits per employee than non-traders in manufacturing sectors in the Netherlands and in Finland. In all other regressions
for the Netherlands we find significant and negative trade premia with small
magnitudes, both in manufacturing and in wholesale & retail trading sectors. The findings for Finland are less conclusive, with trade premia varying
between not significantly different from zero to small but negative, both in
manufacturing and services sectors. The higher persistence of exporting and
significantly smaller sample sizes in Finland than in the Netherlands can also
partially explain the insignificant results for Finland.
Now that we have an indication of the direction of the relationship between trade status and profitability, we turn to the results of the fixed ef11
fects estimations, in order to be able to control for non-observed firm-specific
heterogeneity. Tables 2 and 3 show the results from the fixed effects regressions on the relative gross profit margin as a measure for profitability.
Finnish manufacturing and service sectors both consistently return insignificant trade premia, whereas the picture emerging for the Netherlands is more
mixed. Manufacturing sectors show significantly negative premia for both
sole importers, sole exporters and two-way traders, which is entirely on account of micro firms. In wholesale & retail trading we also find significantly
negative premia, although the separate regressions for firm size classes show
that the picture emerging is most pronounced for small firms and particularly
persistent for two-way trading. While the results for Finland are all insignificant, especially for manufacturing sectors the coefficients are negative. The
insignificance of the results can result also from the relatively small sample
sizes. Similarly, the samples of medium sized and large firms for the Netherlands are relatively small and their results are consistently insignificant.
Table 2: Relative gross profit margin premia (Finland, fixed effects panel
regressions, 2005-2010)
all
manufacturing sectors
micro
small
medium
service sectors
small
medium
large
all
micro
large
reference
reference
reference
reference
reference
0.020
(1.12)
-0.002
(-0.06)
0.038
(1.23)
0.013
(0.76)
0.003
(0.24)
0.009
(0.41)
0.032
(0.80)
-0.010
(-0.34)
0.005
(0.26)
-0.003
(-0.26)
trade dummies
non-trader
reference
reference
reference
reference
reference
only exports
-0.008
(-1.68)
-0.009
(-1.03)
-0.007
(-1.20)
-0.005
(-0.31)
.
.
only imports
-0.006
(-1.00)
-0.007
(-0.57)
-0.001
(-0.46)
-0.010
(-1.52)
-0.010
(-0.29)
two-way trader
-0.001
(-0.12)
-0.001
(-0.10)
-0.002
(-0.52)
0.006
(0.35)
0.025
(1.02)
services exporter
control variables
0.041∗
(2.20)
0.031
(0.66)
0.054
(1.95)
0.021
(0.62)
0.090
(1.35)
0.284
(1.10)
0.780
(1.00)
0.117
(0.75)
0.086
(1.68)
0.020
(0.44)
firm size (fte, log)
0.034∗∗∗
(7.35)
0.043∗∗∗
(5.70)
0.031∗∗∗
(4.39)
0.043
(1.70)
0.109∗∗
(2.71)
0.054∗∗∗
(4.42)
0.058
(1.90)
0.081∗
(2.42)
-0.014
(-0.49)
0.005
(0.34)
domestic firm
reference
reference
reference
reference
reference
reference
reference
reference
reference
reference
multinational
0.006
(0.21)
-0.009
(-0.11)
0.176
(0.96)
-0.025
(-1.13)
-0.037
(-0.85)
-0.009
(-0.13)
-0.011
(-0.13)
0.063
(0.59)
-0.005
(-0.22)
0.021
(0.27)
0.067∗∗∗
(13.36)
0.080∗∗∗
(6.90)
0.066∗∗∗
(10.26)
0.048∗∗
(3.18)
0.023∗∗∗
(5.26)
0.107∗∗∗
(8.73)
0.111∗∗∗
(5.42)
0.101∗∗∗
(3.61)
0.064∗∗∗
(4.76)
0.028
(1.90)
57,787
0.155
0.042
0.054
24,180
0.144
0.059
0.057
25,319
0.224
0.061
0.093
6,686
0.206
0.073
0.071
1,602
0.297
0.021
0.049
62,261
0.032
0.009
0.014
31,769
0.046
0.011
0.015
23,549
0.035
0.000
0.002
5,388
0.540
0.026
0.094
1,555
0.767
0.026
0.103
export share
labor productivity (log)
No. of observations
R2 - within
R2 - between
R2 - overall
Notes: All regressions include a full set of year-sector dummies and fixed effects at firm level. t statistics in parentheses.
p < 0.001
∗
p < 0.05,
∗∗
p < 0.01,
∗∗∗
For manufacturing sectors both in Finland and in the Netherlands, and
similar to the findings of Fryges and Wagner (2010) regarding Germany, we
find a significant and positive coefficient for export share in total sales. This
12
indicates that exporting per se does not necessarily foster profitability rather
than the extent to which foreign markets add to firm sales. This observation
makes sense in the context of the fixed costs associated with exporting, which
thus renders exporting profitable once a certain threshold share of exports
in turnover is reached. In addition, contrary to the OLS-results, we find a
consistently positive and significant correlation between firm size (within the
size category) and profitability. This makes sense intuitively, since larger
firms are for example more likely to be able to exploit economies of scale opportunities.10 Furthermore, productivity remains an important indicator for
profitability in the fixed effects regressions, considering the relatively large,
positive and significant coefficients, which is an intuitively straightforward
finding.
Table 3: Relative gross profit margin premia (the Netherlands, fixed effects
panel regressions, 2002-2010)
all
manufacturing sectors
micro
small
medium
large
all
wholesale and retail trading sectors
micro
small
medium
large
trade dummies
non-trader
reference
reference
reference
reference
reference
reference
reference
reference
reference
reference
only exports
-0.004∗∗
(-3.12)
-0.008∗∗∗
(-3.42)
0.001
(0.31)
-0.007
(-1.32)
-0.019
(-1.07)
-0.003∗
(-2.54)
-0.003
(-1.61)
-0.003
(-1.32)
0.002
(0.42)
-0.035
(-1.11)
only imports
-0.002∗
(-2.40)
-0.003∗
(-2.02)
-0.001
(-1.05)
-0.001
(-0.22)
-0.002
(-0.21)
-0.002∗∗
(-2.91)
-0.002
(-1.78)
-0.005∗∗
(-3.15)
0.006
(1.35)
-0.022
(-0.55)
two-way trader
-0.004∗∗
(-3.28)
-0.005∗
(-2.29)
-0.001
(-0.81)
-0.005
(-1.05)
-0.020
(-1.57)
-0.005∗∗∗
(-4.48)
-0.004∗∗
(-2.64)
-0.007∗∗∗
(-3.75)
0.007
(1.30)
-0.018
(-0.40)
export share
0.022∗∗∗
(4.24)
0.003
(0.30)
0.020∗∗
(2.75)
0.053∗∗∗
(3.68)
0.109
(1.54)
0.005
(1.09)
-0.010
(-1.48)
0.021∗∗
(3.02)
0.022
(1.12)
-0.025
(-0.20)
firm size (fte, log)
0.054∗∗∗
(41.69)
0.064∗∗∗
(30.30)
0.044∗∗∗
(20.87)
0.036∗∗∗
(5.64)
0.012
(0.61)
0.044∗∗∗
(38.10)
0.048∗∗∗
(26.80)
0.039∗∗∗
(17.96)
0.029∗∗∗
(3.95)
-0.006
(-0.41)
domestically controlled
reference
reference
reference
reference
reference
reference
reference
reference
reference
reference
0.006
(1.75)
0.015
(1.96)
0.006
(1.19)
0.007
(0.89)
-0.006
(-0.38)
0.001
(0.43)
-0.005
(-0.74)
0.003
(0.88)
0.013
(1.51)
-0.001
(-0.08)
labor productivity (log)
0.089∗∗∗
(64.05)
0.104∗∗∗
(49.90)
0.076∗∗∗
(33.61)
0.053∗∗∗
(10.31)
0.025∗∗∗
(3.31)
0.069∗∗∗
(61.25)
0.073∗∗∗
(49.94)
0.064∗∗∗
(30.44)
0.045∗∗∗
(8.15)
0.014∗
(2.13)
No. of observations
R2 - within
R2 - between
R2 - overall
269,122
0.253
0.003
0.015
144,467
0.265
0.017
0.026
109,596
0.249
0.055
0.105
13,810
0.216
0.065
0.080
1,249
0.449
0.000
0.006
214,651
0.232
0.027
0.044
138,255
0.238
0.047
0.064
68,613
0.227
0.119
0.158
7,095
0.175
0.096
0.101
688
0.221
0.036
0.066
control variables
foreign controlled
Notes: All regressions include a full set of year-sector dummies and fixed effects at firm level. t statistics in parentheses.
p < 0.001
∗
p < 0.05,
∗∗
p < 0.01,
∗∗∗
Tables 4 and 5 present the results of the same fixed effects regression
10
Firm size is less likely to heavily affect access to capital and capital costs, since access to capital markets for SMEs is relatively easy in both Finland and the Netherlands.
Specifically in developing countries capital market frictions tend to be larger, which is
particularly problematic for smaller firms (Foellmi and Oechslin, 2010). Variation in results between firm size classes is therefore less likely to stem from differences in access to
capital.
13
model, only with relative net profit margin as the dependent variable. The
results regarding the relationship between internationalization and profitability align closely with the findings regarding the relative gross profit margin.
Again we find insignificant premia for Finland and significantly negative but
small premia mainly for smaller firms in the Netherlands. That is, except for
only exporting or importing wholesale & retail traders, who show insignificant premia. In addition, the results regarding the control variables also
resemble the findings regarding the gross profit margin closely.
Table 4: Relative net profit margin premia (Finland, fixed effects panel
regressions, 2005-2010)
all
manufacturing sectors
micro
small
medium
service sectors
small
medium
large
all
micro
large
reference
reference
reference
reference
reference
0.258
(0.89)
0.416
(0.83)
0.015
(0.75)
-0.004
(-0.50)
0.009
(0.77)
0.051
(0.79)
0.078
(0.73)
-0.003
(-0.17)
-0.010
(-1.08)
-0.001
(-0.07)
trade dummies
non-trader
reference
reference
reference
reference
reference
only exports
-0.002
(-0.35)
-0.002
(-0.38)
-0.004
(-0.48)
-0.008
(-0.57)
.
.
only imports
0.003
(0.45)
-0.002
(-0.66)
0.018
(0.71)
-0.013
(-1.79)
0.005
(0.30)
two-way trader
-0.004
(-0.90)
-0.003
(-0.45)
-0.001
(-0.13)
-0.008
(-1.26)
0.017
(0.76)
services exporter
control variables
-0.212
(-1.04)
-0.004
(-0.16)
-0.407
(-0.96)
-0.045∗
(-2.07)
-0.087∗
(-2.10)
-0.052
(-0.36)
-0.232
(-0.50)
-0.199
(-1.22)
0.032
(0.82)
-0.023
(-0.39)
firm size (fte, log)
0.018∗∗∗
(4.27)
0.042∗∗∗
(6.70)
0.032∗∗
(3.00)
0.005
(0.41)
0.029
(1.37)
0.042∗
(2.46)
-0.236
(-0.64)
0.054∗∗
(2.63)
0.006
(0.50)
-0.000
(-0.01)
domestic firm
reference
reference
reference
reference
reference
reference
reference
reference
reference
reference
multinational
-0.008
(-0.32)
-0.044
(-0.38)
0.039
(0.98)
-0.007
(-0.42)
-0.025
(-0.64)
8.911
(0.84)
20.568
(0.80)
0.053
(0.79)
0.023
(0.88)
-0.009
(-0.29)
0.081∗∗∗
(10.23)
0.077∗∗∗
(14.56)
0.111∗∗∗
(4.20)
0.053∗∗∗
(5.90)
0.047∗∗∗
(5.84)
0.139∗∗∗
(4.49)
0.109∗∗∗
(3.91)
0.123∗∗∗
(7.41)
0.082∗∗∗
(6.34)
0.030
(1.48)
57,962
0.059
0.120
0.066
24,278
0.276
0.131
0.122
25,402
0.060
0.062
0.044
6,680
0.370
0.035
0.017
1,602
0.530
0.395
0.430
62,704
0.030
0.003
0.000
32,022
0.039
0.000
0.000
23,687
0.739
0.397
0.490
5,429
0.989
0.942
0.965
1,566
0.991
0.635
0.016
export share
labor productivity (log)
No. of observations
R2 - within
R2 - between
R2 - overall
Notes: All regressions include a full set of year-sector dummies and fixed effects at firm level. t statistics in parentheses.
p < 0.001
14
∗
p < 0.05,
∗∗
p < 0.01,
∗∗∗
Table 5: Relative net profit margin premia (the Netherlands, fixed effects
panel regressions, 2002-2010)
all
manufacturing sectors
micro
small
medium
large
all
wholesale and retail trading sectors
micro
small
medium
large
trade dummies
non-trader
reference
reference
reference
reference
reference
reference
reference
reference
reference
reference
only exports
-0.005∗∗
(-3.20)
-0.008∗∗
(-3.18)
-0.000
(-0.17)
-0.006
(-1.03)
-0.029
(-1.41)
-0.002
(-1.08)
-0.001
(-0.27)
-0.001
(-0.61)
0.004
(0.68)
-0.009
(-0.26)
only imports
-0.002∗
(-2.11)
-0.003
(-1.72)
-0.002
(-1.12)
0.001
(0.19)
-0.010
(-0.71)
-0.002
(-1.83)
-0.001
(-0.60)
-0.004∗∗
(-2.72)
0.007
(1.24)
0.010
(0.26)
-0.005∗∗∗
(-3.70)
-0.007∗∗
(-3.06)
-0.002
(-1.26)
-0.001
(-0.13)
-0.027
(-1.75)
-0.003∗∗
(-2.79)
-0.002
(-1.04)
-0.006∗∗
(-2.97)
0.006
(1.07)
0.019
(0.44)
export share
0.016∗∗
(2.77)
-0.002
(-0.20)
0.009
(1.14)
0.049∗∗
(3.08)
0.184
(1.36)
0.006
(1.23)
-0.003
(-0.47)
0.018∗
(2.29)
0.001
(0.06)
-0.168
(-0.75)
firm size (fte, log)
0.069∗∗∗
(47.78)
0.081∗∗∗
(34.00)
0.059∗∗∗
(25.96)
0.042∗∗∗
(5.99)
0.021
(1.02)
0.053∗∗∗
(42.00)
0.059∗∗∗
(30.82)
0.047∗∗∗
(19.56)
0.036∗∗∗
(4.50)
-0.007
(-0.41)
domestically controlled
reference
reference
reference
reference
reference
reference
reference
reference
reference
reference
0.008
(1.88)
0.011
(1.19)
0.008
(1.43)
0.007
(0.81)
-0.006
(-0.28)
-0.000
(-0.03)
-0.009
(-1.14)
0.004
(1.09)
0.007
(0.81)
-0.010
(-0.59)
labor productivity (log)
0.111∗∗∗
(71.82)
0.127∗∗∗
(52.91)
0.101∗∗∗
(41.44)
0.066∗∗∗
(10.81)
0.027∗∗
(2.96)
0.083∗∗∗
(64.83)
0.089∗∗∗
(52.86)
0.079∗∗∗
(33.43)
0.061∗∗∗
(7.65)
0.011
(1.42)
No. of observations
R2 - within
R2 - between
R2 - overall
269,362
0.285
0.011
0.030
144,558
0.294
0.024
0.038
109,727
0.293
0.100
0.160
13,830
0.233
0.089
0.106
1,247
0.442
0.003
0.018
214,796
0.264
0.051
0.075
138,327
0.270
0.074
0.095
68,684
0.264
0.167
0.204
7,097
0.209
0.104
0.127
688
0.178
0.006
0.026
two-way trader
control variables
foreign controlled
Notes: All regressions include a full set of year-sector dummies and fixed effects at firm level. t statistics in parentheses.
p < 0.001
∗
p < 0.05,
∗∗
p < 0.01,
∗∗∗
The regressions with relative return on assets (ROA) as the profitability
measure under investigation return consistent results as well (tables 6 and
7). Again, we find insignificant trade premia for Finnish firms and significantly negative trade premia in the Netherlands, in both manufacturing and
wholesale & retail trading, mainly on account of smaller firms. The findings
regarding the control variables are robust to the alternative profit measure
employed, with firm size, productivity and, to a lesser extent, the export
share in sales being positively associated with the return on assets.
15
Table 6: Relative return on assets premia (Finland, fixed effects panel regressions, 2005-2010)
all
manufacturing sectors
micro
small
medium
service sectors
small
medium
large
all
micro
large
reference
reference
reference
reference
reference
-0.007
(-0.84)
-0.008
(-0.57)
-0.003
(-0.24)
0.004
(0.10)
-0.001
(-0.03)
0.012
(1.52)
0.014
(1.01)
-0.005
(-0.44)
0.014
(0.45)
-0.007
(-0.15)
trade dummies
non-trader
reference
reference
reference
reference
reference
only exports
-0.008
(-0.91)
-0.004
(-0.28)
-0.017
(-1.09)
-0.057
(-0.96)
.
.
only imports
-0.003
(-0.75)
-0.001
(-0.09)
-0.003
(-0.50)
-0.009
(-0.55)
-0.002
(-0.04)
two-way trader
-0.009
(-1.51)
-0.014
(-1.12)
-0.000
(-0.05)
-0.016
(-0.96)
0.007
(0.22)
services exporter
control variables
export share
0.001
(0.06)
0.053
(1.18)
0.008
(0.26)
-0.014
(-0.36)
-0.085
(-1.12)
0.012
(0.44)
0.051
(0.90)
0.002
(0.05)
0.035
(0.40)
0.071
(0.46)
firm size (fte, log)
0.036∗∗∗
(5.93)
0.047∗∗
(3.24)
0.044∗∗∗
(3.85)
0.054∗
(2.26)
0.092∗∗
(2.99)
0.066∗∗∗
(8.11)
0.069∗∗∗
(3.74)
0.062∗∗∗
(3.58)
0.094∗
(2.16)
0.187∗∗
(2.60)
domestic firm
reference
reference
reference
reference
reference
reference
reference
reference
reference
reference
multinational
-0.020
(-0.56)
-0.454∗∗∗
(-12.85)
0.056
(0.78)
-0.031
(-0.74)
-0.046
(-0.70)
-0.080
(-1.62)
-0.114
(-0.97)
-0.042
(-0.47)
0.166
(1.67)
-0.047
(-0.58)
0.057∗∗∗
(20.67)
0.067∗∗∗
(11.71)
0.064∗∗∗
(12.88)
0.048∗∗∗
(5.50)
0.041∗∗∗
(3.71)
0.068∗∗∗
(19.69)
0.069∗∗∗
(12.15)
0.064∗∗∗
(11.15)
0.083∗∗∗
(4.57)
0.084∗∗
(2.75)
43,584
0.090
0.035
0.024
17,100
0.103
0.075
0.058
19,606
0.105
0.048
0.037
5,476
0.148
0.033
0.050
1,402
0.241
0.000
0.035
49,333
0.068
0.062
0.041
24,317
0.069
0.092
0.065
19,124
0.074
0.060
0.051
4,520
0.110
0.008
0.006
1,372
0.124
0.015
0.003
labor productivity (log)
No. of observations
R2 - within
R2 - between
R2 - overall
Notes: All regressions include a full set of year-sector dummies and fixed effects at firm level. t statistics in parentheses.
p < 0.001
16
∗
p < 0.05,
∗∗
p < 0.01,
∗∗∗
Table 7: Relative return on assets premia (the Netherlands, fixed effects
panel regressions, 2002-2010)
all
manufacturing sectors
micro
small
medium
large
all
wholesale and retail trading sectors
micro
small
medium
large
trade dummies
non-trader
reference
reference
reference
reference
reference
reference
reference
reference
reference
reference
only exports
-0.008∗∗∗
(-3.96)
-0.008∗
(-2.24)
-0.003
(-1.15)
-0.015
(-1.55)
-0.084
(-1.79)
-0.007∗∗
(-3.15)
-0.005
(-1.78)
-0.008∗
(-2.45)
-0.007
(-0.69)
-0.057
(-0.91)
only imports
-0.005∗∗
(-3.17)
-0.005∗
(-2.04)
-0.003
(-1.24)
-0.006
(-0.73)
-0.024
(-0.95)
-0.007∗∗∗
(-4.65)
-0.006∗∗
(-2.87)
-0.005
(-1.89)
-0.006
(-0.72)
-0.024
(-0.33)
two-way trader
-0.008∗∗∗
(-3.93)
-0.007∗
(-1.97)
-0.004
(-1.53)
-0.020∗
(-2.35)
-0.044
(-1.63)
-0.013∗∗∗
(-6.80)
-0.013∗∗∗
(-5.05)
-0.011∗∗∗
(-3.59)
-0.003
(-0.28)
-0.023
(-0.30)
export share
0.030∗∗∗
(4.33)
0.004
(0.31)
0.033∗∗∗
(3.32)
0.041∗
(2.53)
0.084
(1.61)
-0.008
(-1.39)
-0.007
(-0.88)
-0.001
(-0.12)
-0.006
(-0.31)
-0.063
(-0.47)
firm size (fte, log)
0.047∗∗∗
(25.04)
0.065∗∗∗
(17.80)
0.030∗∗∗
(9.67)
0.032∗∗∗
(3.37)
0.009
(0.31)
0.057∗∗∗
(30.01)
0.063∗∗∗
(20.39)
0.049∗∗∗
(14.18)
0.056∗∗∗
(5.52)
0.034
(1.17)
domestically controlled
reference
reference
reference
reference
reference
reference
reference
reference
reference
reference
0.012∗
(2.19)
0.024
(1.92)
0.006
(0.75)
0.014
(1.67)
-0.004
(-0.14)
0.009∗
(2.10)
0.005
(0.48)
0.015∗∗
(2.88)
0.016
(1.61)
0.024
(0.96)
labor productivity (log)
0.104∗∗∗
(59.49)
0.125∗∗∗
(47.07)
0.086∗∗∗
(33.14)
0.070∗∗∗
(12.19)
0.033∗∗∗
(3.78)
0.110∗∗∗
(65.55)
0.122∗∗∗
(54.25)
0.098∗∗∗
(31.96)
0.076∗∗∗
(12.07)
0.037∗∗
(3.32)
No. of observations
R2 - within
R2 - between
R2 - overall
266,520
0.176
0.002
0.002
142,162
0.155
0.000
0.001
109,301
0.205
0.028
0.082
13,812
0.210
0.084
0.117
1,245
0.351
0.073
0.093
213,518
0.219
0.004
0.020
137,193
0.200
0.008
0.017
68,545
0.264
0.123
0.194
7,094
0.307
0.144
0.201
686
0.341
0.032
0.100
control variables
foreign controlled
Notes: All regressions include a full set of year-sector dummies and fixed effects at firm level. t statistics in parentheses.
p < 0.001
∗
p < 0.05,
∗∗
p < 0.01,
∗∗∗
The results regarding the relative gross profit margin per employee show
both the scale effect of exporting and the margin effect (see section 4.1). Using the relative gross profit margin per employee as a measure of profitability,
we find significant and negative trade premia for Dutch micro firms that solely
export (tables 8 and 9). All other trade dummy variables return insignificant
coefficients both for Finland and for the Netherlands in comparison to the
negative margin effects especially in the Netherlands. A particularly striking finding is that the relationship between firm size and profitability turns
negative and significant both in Finland and in the Netherlands except for
Dutch wholesale & retail trading sectors. In addition, the export share returns mixed results, showing a significant and positive coefficient in Finnish
manufacturing, a significant and negative coefficient in Dutch wholesale &
retail trading and insignificant estimates otherwise.
17
Table 8: Relative gross profit per employee premia (Finland, fixed effects
panel regressions, 2005-2010)
all
manufacturing sectors
micro
small
medium
large
all
micro
service sectors
small
medium
large
trade dummies
non-trader
only exports
reference
-251.339
(-0.54)
reference
-178.835
(-0.28)
reference
50.410
(0.08)
reference
-2401.323
(-1.25)
reference
.
.
reference
reference
reference
reference
reference
only imports
12.281
(0.05)
731.547∗
(1.97)
-7.189
(-0.02)
-624.398
(-0.27)
4629.513
(0.99)
678.509
(1.50)
847.651
(1.01)
217.839
(0.33)
713.156
(0.55)
-1831.040
(-0.75)
-481.200
(-1.40)
-300.600
(-0.41)
-216.663
(-0.49)
-2614.016
(-1.48)
2060.379
(0.53)
-402.765
(-0.74)
-26.889
(-0.03)
-157.305
(-0.18)
134.974
(0.12)
-5310.153
(-1.23)
8162.633
(0.59)
1222.989
(0.71)
1869.674
(0.70)
-1259.463
(-0.39)
3587.315
(0.77)
7520.044
(0.78)
7335.230
(1.16)
-2046.390∗∗∗
-4952.920∗∗∗
(-4.21)
(-4.63)
-2073.035
(-1.52)
-182.517
(-0.11)
196.513
(0.12)
two-way trader
services exporter
control variables
export share
4562.729∗∗∗
(3.46)
4312.215
(1.51)
3413.993
(1.79)
firm size (fte, log)
-4220.541∗∗∗
-6193.727∗∗∗
-4154.308∗∗∗
(-6.78)
(-9.32)
(-5.16)
-13698.127
(-1.15)
domestic firm
reference
reference
reference
reference
reference
reference
reference
reference
reference
reference
multinational
-2288.302
(-0.66)
1552.982
(0.19)
11556.509∗
(2.40)
1762.787
(0.51)
-5770.975
(-0.89)
3363.333
(0.38)
24769.121
(0.70)
-10030.585
(-0.80)
8929.274
(1.03)
772.103
(0.13)
5692.438∗∗∗
(7.16)
4530.430∗∗∗
(14.54)
5614.964∗∗∗
(9.14)
14450.056
(1.67)
9919.018∗∗
(3.18)
4531.138∗∗∗
(14.89)
4682.371∗∗∗
(9.06)
4532.406∗∗∗
(8.31)
4637.188∗∗∗
(4.43)
6130.764∗
(2.40)
58,864
0.091
0.018
0.019
24,827
0.194
0.175
0.131
25,768
0.076
0.076
0.057
6,707
0.211
0.005
0.011
1,562
0.377
0.018
0.073
63,757
0.070
0.025
0.032
32,502
0.079
0.029
0.033
24,106
0.088
0.012
0.012
5,535
0.178
0.014
0.025
1,614
0.178
0.075
0.110
labor productivity (log)
No. of observations
R2 - within
R2 - between
R2 - overall
13203.479
(1.61)
Notes: All regressions include a full set of year-sector dummies and fixed effects at firm level. t statistics in parentheses.
∗
p < 0.05,
∗∗
p < 0.01,
∗∗∗
p < 0.001
Table 9: Relative gross profit per employee premia (the Netherlands, fixed
effects panel regressions, 2002-2010)
all
manufacturing sectors
micro
small
medium
large
wholesale and retail trading sectors
micro
small
medium
all
large
trade dummies
non-trader
reference
reference
reference
reference
reference
reference
reference
reference
reference
reference
only exports
-515.546∗∗
(-3.12)
-886.631∗∗
(-3.20)
-22.634
(-0.11)
-573.621
(-0.94)
-1815.836
(-0.71)
-511.339∗
(-2.26)
-636.691∗
(-2.10)
-142.324
(-0.41)
-1092.674
(-1.21)
-8920.504
(-1.50)
only imports
-175.208
(-1.54)
-291.999
(-1.69)
-23.593
(-0.15)
-462.473
(-0.73)
974.935
(0.52)
-197.577
(-1.71)
-185.351
(-1.31)
-106.724
(-0.53)
-753.026
(-1.13)
-12544.983
(-1.70)
two-way trader
-181.327
(-1.09)
-78.548
(-0.28)
-35.233
(-0.16)
-1294.702
(-1.85)
-3256.853
(-1.76)
-280.766
(-1.51)
-57.864
(-0.23)
-485.841
(-1.68)
-630.935
(-0.79)
-11141.696
(-1.38)
829.641
(1.07)
-779.890
(-0.54)
1214.827
(1.17)
3699.775
(1.57)
5602.568
(0.80)
-1982.706∗
(-2.36)
-2807.367∗
(-2.32)
-360.304
(-0.28)
2870.545
(0.80)
18411.557
(1.31)
-1008.612∗∗∗
(-6.37)
-1717.211∗∗∗
(-6.88)
-987.365∗∗∗
(-3.84)
-1528.525
(-1.57)
-6123.684
(-1.69)
84.438
(0.40)
-586.861
(-1.94)
78.190
(0.20)
165.317
(0.12)
-5419.311
(-1.61)
domestically controlled
reference
reference
reference
reference
reference
reference
reference
reference
reference
reference
foreign controlled
348.086
(0.61)
1313.471
(0.83)
-524.750
(-0.59)
796.355
(0.89)
1405.490
(0.64)
1126.807∗
(2.13)
2147.512∗
(2.08)
814.504
(1.22)
2427.024
(1.43)
995.267
(0.37)
10497.125∗∗∗
(66.01)
11748.085∗∗∗
(51.02)
8868.796∗∗∗
(37.47)
9272.986∗∗∗
(13.99)
7127.940∗∗∗
(3.35)
14549.537∗∗∗
(71.13)
14815.894∗∗∗
(59.38)
14128.063∗∗∗
(35.32)
12594.467∗∗∗
(12.90)
6132.424∗∗∗
(3.35)
269,594
0.241
0.191
0.210
145,404
0.269
0.224
0.229
109,289
0.202
0.196
0.216
13,685
0.189
0.132
0.154
1,216
0.367
0.002
0.041
212,476
0.302
0.291
0.317
137,040
0.310
0.301
0.313
67,833
0.278
0.339
0.367
6,930
0.242
0.249
0.246
673
0.207
0.139
0.145
control variables
export share
firm size (fte, log)
labor productivity (log)
No. of observations
R2 - within
R2 - between
R2 - overall
Notes: All regressions include a full set of year-sector dummies and fixed effects at firm level. t statistics in parentheses.
∗
p < 0.05,
∗∗
p < 0.01,
∗∗∗
p < 0.001
We draw a few preliminary conclusions from the regression results presented in this section:
• Internationalization does not seem to be heavily correlated with profitability, considering the largely insignificant or significantly negative
18
but relatively small trade premia;
• The negative trade premia seem to be tied mainly to exporting rather
than to importing;
• The choice for the profit measure under investigation does not heavily
affect the findings;
• Productivity and firm size are important indicators for firm-level profitability;
• Profits tend to increase in the share of exports in total sales;
• The overall quality and performance of the fixed effects regressions
indicate that the relative gross and net profit margins and return on
assets yield the most consistent and robust results.
Exporter churning might provide a partial explanation for the lack of positive
profitability premia. If a relatively large fraction of firms starts exporting
or switches trade status frequently, the relative impact of the fixed costs
associated with an export start will be high, which could drive down profits
relative to non-exporters. In addition, relative to the Netherlands, exporting
among Finnish firms is more persistent, which, paired with a considerably
smaller number of observations, could imply that the amount of variance
left in the data is insufficient to yield any significant findings regarding the
relationship between trade status and profitability.
5.2
Propensity score matching results
In line with the fixed effects estimation results, the propensity score matching analysis shows no discernible difference between export starters and firms
that keep their focus on domestic markets in terms of profitability in the years
following foreign market entry. Tables 10 through 13 present the accompanying results of this analysis.
Particularly regarding Finland we find virtually no empirical evidence
suggesting that Finnish export starters convert to a different profitability
growth path relative to continuing non-exporters (tables 10 and 11). Out
of 96 investigated combinations of cohort and outcome variable we find just
three significant treatment effects. Manufacturing firms that entered foreign
markets in 2007 show consistently lower gross profit margins and growth
rates following export market entry, ultimately resulting in a significantly
lower gross profit margin after three years. In addition, manufacturing firms
entering foreign markets in 2008 show significantly higher return on assets
growth one year after export start and service providers from the same cohort return a significantly higher ROA in the year of treatment. However,
in the years following this cohort of firms returns lower growth rates, quickly
rendering the treatment effect insignificant. These three isolated cases pro19
vide no solid basis supporting the claim that firms entering export markets
convert to a different profitability path, neither higher nor lower, than firms
that keep focusing solely on domestic markets.
Table 10: The effect of exporting on profitability in manufacturing sectors
in Finland
export start
in year t
outcome variable
relative gross profit margin
no. of matched
treated firms
ATT (%)
relative net profit margin
no. of matched
treated firms
ATT (%)
relative return on assets
no. of matched
treated firms
ATT (%)
2007
prof itlevel at time t
prof itgrowtht,t+1 (percentage point change)
prof itlevel at time t+1
prof itgrowtht+1,t+2 (percentage point change)
prof itlevel at time t+2
prof itgrowtht+2,t+3 (percentage point change)
profit level at time t+3
263
141
139
99
100
66
67
-1.96
-0.09
-10.71
-4.34
-4.62
-3.56
-11.72∗
262
140
140
101
100
66
66
0.43
0.21
0.02
-0.23
-1.57
-5.46
-4.59
262
138
138
97
99
65
66
-0.08
4.48
14.86
-4.00
-1.01
-6.02
-6.49
2008
prof itlevel at time t
prof itgrowtht,t+1 (percentage point change)
prof itlevel at time t+1
prof itgrowtht+1,t+2 (percentage point change)
prof itlevel at time t+2
214
87
88
62
71
-2.02
0.65
-1.78
-1.87
-4.06
224
89
88
65
72
-2.95
-0.19
-1.29
-0.77
-2.29
216
87
88
64
72
-4.50
5.78∗
-1.84
-0.91
-2.27
2009
prof itlevel at time t
prof itgrowtht,t+1 (percentage point change)
prof itlevel at time t+1
231
105
105
-1.32
-2.08
-0.20
244
106
108
-0.78
-0.65
-0.72
235
104
107
0.13
-1.89
-1.62
2010
prof itlevel at time t
258
-1.12
264
0.14
257
1.40
Notes: Nearest neighbor propensity score matching was done using Stata 11 and the psmatch2 package developed by Leuven and Sianesi (2003). The common
support condition is imposed on the matching procedure, implying that treated firms with a propensity score higher than the maximum of the non-treated control
group and lower than the minimum of the control group are taken off support and are not matched to a peer. The balancing property condition, requiring absence
of statistically significant differences between the means of the matching characteristics of the firms in the treatment and the control group is fully satisfied in all
instances. The bias-corrected 95% confidence intervals are generated by bootstrapping the ATT with 200 replications. ∗ p < 0.05
Table 11: The effect of exporting on profitability in service sectors in Finland
export start
in year t
outcome variable
relative gross profit margin
no. of matched
treated firms
ATT (%)
relative net profit margin
no. of matched
treated firms
ATT (%)
relative return on assets
no. of matched
treated firms
ATT (%)
2007
prof itlevel at time t
prof itgrowtht,t+1 (percentage point change)
prof itlevel at time t+1
prof itgrowtht+1,t+2 (percentage point change)
prof itlevel at time t+2
prof itgrowtht+2,t+3 (percentage point change)
prof itlevel at time t+3
353
185
185
130
141
93
93
-2.04
-8.22
-14.92
-15.18
-16.68
0.18
4.51
358
187
187
129
142
93
92
0.78
-0.03
-3.19
-0.40
-2.79
-1.30
-1.01
354
188
188
131
141
93
93
1.60
6.81
25.53
9.55
-0.88
-0.11
2.76
2008
prof itlevel at time t
prof itgrowtht,t+1 (percentage point change)
prof itlevel at time t+1
prof itgrowtht+1,t+2 (percentage point change)
prof itlevel at time t+2
331
166
166
108
111
-1.73
1.21
0.64
2.48
-1.76
343
168
168
109
115
-1.16
1.13
0.77
1.36
-6.10
331
166
168
109
117
8.47∗
-7.53
3.13
-1.17
2.22
2009
prof itlevel at time t
prof itgrowtht,t+1 (percentage point change)
prof itlevel at time t+1
350
190
195
-1.33
2.30
0.52
358
191
193
-3.65
-0.21
-5.12
346
196
197
-1.66
0.38
-3.11
2010
prof itlevel at time t
616
-3.61
625
0.49
620
1.63
Notes: Nearest neighbor propensity score matching was done using Stata 11 and the psmatch2 package developed by Leuven and Sianesi (2003). The common
support condition is imposed on the matching procedure, implying that treated firms with a propensity score higher than the maximum of the non-treated control
group and lower than the minimum of the control group are taken off support and are not matched to a peer. The balancing property condition, requiring absence
of statistically significant differences between the means of the matching characteristics of the firms in the treatment and the control group is fully satisfied in all
instances. The bias-corrected 95% confidence intervals are generated by bootstrapping the ATT with 200 replications. ∗ p < 0.05
20
Table 12: The effect of exporting on profitability in manufacturing sectors
in the Netherlands
export start
in year t
outcome variable
relative gross profit margin
no. of matched
treated firms
ATT (%)
relative net profit margin
no. of matched
treated firms
ATT (%)
relative return on assets
no. of matched
treated firms
ATT (%)
2004
prof itlevel at time t
prof itgrowtht,t+1 (percentage point change)
prof itlevel at time t+1
prof itgrowtht+1,t+2 (percentage point change)
prof itlevel at time t+2
prof itgrowtht+2,t+3 (percentage point change)
prof itlevel at time t+3
280
94
103
47
49
34
36
0.7
-0.88
0.49
-1.61
-1.87
0.32
0.58
282
96
104
47
49
35
36
-0.18
-0.41
0.29
-0.89
-2.2
-0.82
-0.12
283
99
102
47
49
35
36
0.76
-0.11
1.83
-1.22
-2.57
-1.55
-0.5
2005
prof itlevel at time t
prof itgrowtht,t+1 (percentage point change)
prof itlevel at time t+1
prof itgrowtht+1,t+2 (percentage point change)
prof itlevel at time t+2
prof itgrowtht+2,t+3 (percentage point change)
prof itlevel at time t+3
280
84
94
51
55
42
43
-0.24
0.68
0.61
0.16
3.4
-0.63
2.57
280
86
95
50
55
42
43
1.65
0.5
1.81
0.38
3.56
-1.12
1.42
278
88
95
53
55
42
43
0.75
2.3
1.43
1.01
1.49
2.06
3.24
2006
prof itlevel at time t
prof itgrowtht,t+1 (percentage point change)
prof itlevel at time t+1
prof itgrowtht+1,t+2 (percentage point change)
prof itlevel at time t+2
prof itgrowtht+2,t+3 (percentage point change)
prof itlevel at time t+3
233
87
94
47
51
24
31
-0.93
-0.51
-1.79
0.34
1.56
4.85∗
3.49
232
87
94
45
51
26
31
-0.78
-0.62
-1.04
0.11
0.3
2.76
3.34
232
90
93
49
51
28
31
-0.89
-1.93
0.14
-0.71
0.91
4.51∗
1.91
2007
prof itlevel at time t
prof itgrowtht,t+1 (percentage point change)
prof itlevel at time t+1
prof itgrowtht+1,t+2 (percentage point change)
prof itlevel at time t+2
prof itgrowtht+2,t+3 (percentage point change)
prof itlevel at time t+3
244
117
128
52
66
40
48
-0.33
-0.55
-2.19
-0.47
-1.83
2.97∗
2.01
244
117
128
55
66
41
48
0.69
-0.91
-1.65
-0.46
-2.16
1.44
0.48
244
120
128
58
66
45
48
-1.08
-1.88
-1.74
0.38
-3.73∗
4.62∗
-2.88
2008
prof itlevel at time t
prof itgrowtht,t+1 (percentage point change)
prof itlevel at time t+1
prof itgrowtht+1,t+2 (percentage point change)
prof itlevel at time t+2
983
442
503
332
366
0.42
-0.51
0.39
1.28∗
2.46∗
983
437
502
320
367
-0.22
-1.11∗
0.53
1.44∗
2.25∗
984
465
502
347
367
-1.25
-0.97∗
-0.08
2.18∗
1.68
2009
prof itlevel at time t
prof itgrowtht,t+1 (percentage point change)
prof itlevel at time t+1
405
146
169
0.54
0.29
3.43
405
144
169
0.12
0.58
3.22∗
404
153
168
0.37
1.74
2.74
2010
prof itlevel at time t
995
-0.51
995
-0.24
988
0.12
Notes: Nearest neighbor propensity score matching was done using Stata 11 and the psmatch2 package developed by Leuven and Sianesi (2003). The common
support condition is imposed on the matching procedure, implying that treated firms with a propensity score higher than the maximum of the non-treated control
group and lower than the minimum of the control group are taken off support and are not matched to a peer. The balancing property condition, requiring absence
of statistically significant differences between the means of the matching characteristics of the firms in the treatment and the control group is fully satisfied in all
instances. The bias-corrected 95% confidence intervals are generated by bootstrapping the ATT with 200 replications. ∗ p < 0.05
The PSM-procedure concerning the Netherlands returns a few more significant results, although the majority of the estimated treatment effects
remains insignificant. In Dutch manufacturing we find some evidence suggesting that export starters materialize higher profit growth rates two to
three years after foreign market entry, on several occasions resulting in significantly higher profit levels as well. Particularly for the 2008-cohort these
findings seem relatively robust, which is most likely mainly due to the relatively large number of available treated cases. Wholesale & retail trading
sectors in the Netherlands show less pronounced profitability patterns. Only
for the 2006-cohort do we find noteworthy treatment effects, particularly for
profit growth in year two and profit levels in year three after foreign market
entry. The findings for the Netherlands thus also provide little evidence in
favor of the hypothesis suggesting the profitability patterns differ between
21
export starters and continuing non-exporters. However, we do find some
empirical evidence suggesting that export starters in Dutch manufacturing
materialize higher profits, particularly in the longer run, that is, two to three
years after foreign market entry.
Table 13: The effect of exporting on profitability in wholesale & retail
trading sectors in the Netherlands
export start
in year t
outcome variable
relative gross profit margin
no. of matched
treated firms
ATT (%)
relative net profit margin
no. of matched
treated firms
ATT (%)
relative return on assets
no. of matched
treated firms
ATT (%)
2004
prof itlevel at time t
prof itgrowtht,t+1 (percentage point change)
prof itlevel at time t+1
prof itgrowtht+1,t+2 (percentage point change)
prof itlevel at time t+2
prof itgrowtht+2,t+3 (percentage point change)
prof itlevel at time t+3
236
93
99
44
45
31
32
-0.79
-0.68
0.45
0.08
1.9
1.74
-1.05
237
95
99
44
45
31
32
-0.5
-1.02
0.18
-0.46
2.67
1.77
-0.45
238
98
99
43
46
32
32
-0.07
-0.46
1.95
-2.3
3.98
0.84
-1.46
2005
prof itlevel at time t
prof itgrowtht,t+1 (percentage point change)
prof itlevel at time t+1
prof itgrowtht+1,t+2 (percentage point change)
prof itlevel at time t+2
prof itgrowtht+2,t+3 (percentage point change)
prof itlevel at time t+3
294
92
98
50
52
38
41
-0.14
-0.84
-0.99
-0.25
0.6
-0.42
-3.12∗
294
92
98
50
52
37
41
0.43
-0.63
-1.15
-0.36
1.02
-0.45
-2.18
293
91
98
49
52
36
41
-0.05
-1.93
-1.72
-0.11
-2.68
-1.93
-3.43
2006
prof itlevel at time t
prof itgrowtht,t+1 (percentage point change)
prof itlevel at time t+1
prof itgrowtht+1,t+2 (percentage point change)
prof itlevel at time t+2
prof itgrowtht+2,t+3 (percentage point change)
prof itlevel at time t+3
217
93
93
62
68
44
45
-1.17
0.12
-0.42
1.76∗
0.7
0.8
5.68∗
217
91
93
62
68
44
45
-0.6
0.27
0.22
1.31∗
1.05
0.8
6.48∗
216
90
92
65
68
44
45
1
2.08
0.87
0.49
4.18
-0.24
5.77∗
2007
prof itlevel at time t
prof itgrowtht,t+1 (percentage point change)
prof itlevel at time t+1
prof itgrowtht+1,t+2 (percentage point change)
prof itlevel at time t+2
prof itgrowtht+2,t+3 (percentage point change)
prof itlevel at time t+3
243
126
130
80
85
64
67
0.41
0.42
-0.24
-0.34
0.1
1.37
2.79
242
128
130
80
85
64
67
0.76
0.03
-0.09
-0.44
1.08
1.08
3.82
243
126
129
81
85
65
67
0.71
0.35
-1.16
-0.26
-1.19
1.47
3.38
2008
prof itlevel at time t
prof itgrowtht,t+1 (percentage point change)
prof itlevel at time t+1
prof itgrowtht+1,t+2 (percentage point change)
prof itlevel at time t+2
822
401
418
312
321
-0.83
0.01
0.38
-0.06
-0.54
822
402
418
316
321
-0.17
-0.16
0.97
0.11
0.34
822
397
419
313
321
-0.55
-0.64
0.49
0.39
1.24
2009
prof itlevel at time t
prof itgrowtht,t+1 (percentage point change)
prof itlevel at time t+1
357
149
161
-0.28
-0.27
1.78
357
150
161
0.16
-0.2
1.72
355
150
159
0.55
0.37
-0.45
2010
prof itlevel at time t
569
0.44
569
0.01
570
0.28
Notes: Nearest neighbor propensity score matching was done using Stata 11 and the psmatch2 package developed by Leuven and Sianesi (2003). The common
support condition is imposed on the matching procedure, implying that treated firms with a propensity score higher than the maximum of the non-treated control
group and lower than the minimum of the control group are taken off support and are not matched to a peer. The balancing property condition, requiring absence
of statistically significant differences between the means of the matching characteristics of the firms in the treatment and the control group is fully satisfied in
all instances. The propensity score for the 2005-cohort is estimated with the control variable for sectors included as a numerical variable instead of a categorical
variable, since the model presented in equation 7 does not converge for this cohort. The bias-corrected 95% confidence intervals are generated by bootstrapping
the ATT with 200 replications. ∗ p < 0.05
The main conclusions we draw from the propensity score matching procedures discussed in this section are the following:
• Exporting does not seem to convincingly foster profitability nor hamper
it;
• Finnish export starters do not seem to convert to a different profitability
path relative to continuing non-traders;
• In the Netherlands there is some evidence suggesting the export starters
22
in manufacturing sectors materialize higher profits in the longer run,
that is, two to three years after foreign market entry.
6
Conclusion
Compiling two parallel data sets covering Dutch firms over the years 20022010 and Finnish firms over the years 2005-2010, we investigate the relationship between trade status, firm size and profitability. We proceed in
two steps. We start by establishing the relationship between exporting and
profitability, irrespective of the direction of causality, by means of regression
analysis and employing four different profit measures. Then we resort to
propensity score matching to investigate whether firms entering foreign markets convert to a different profitability path compared to firms that persevere
in their focus on domestic markets.
The results from the regression analysis suggest that internationalization
of firm activities is not heavily correlated with profitability. We find largely
insignificant or significantly negative trade premia of small magnitude, which
aligns with earlier research. In addition, the negative trade premia seem to
be tied mainly to exporting rather than to importing and particularly to
micro and small firms. The choice of profit measure does not heavily affect
the findings regarding the relationship with trade status. Gross profits per
employee do return slightly deviating profitability premia compared to the
other three profitability measures employed, which generally yield mutually
consistent results. This indicates that the ’scale effect’ of exporting could be
positive or insignificant, while the ’margin effect’ is negative or insignificant
based on the gross margin and net margin results. Regarding the control
variables our findings indicate that particularly productivity and firm size
are important indicators for firm-level profitability. In addition, we show
that profits tend to increase in the share of exports in total sales.
Exporter churning might provide a partial explanation for the lack of
positive profitability premia. If a relatively large fraction of firms starts
exporting or switches trade status frequently, the relative impact of the fixed
costs associated with an export start will be high, which could drive down
profits relative to non-exporters. In addition, relative to the Netherlands,
exporting among Finnish firms is much more persistent, which, paired with
a considerably smaller number of observations, could imply that the amount
of variance left in the data is insufficient to yield any significant findings
regarding the relationship between trade status and profitability.
The results from the propensity score matching analysis show little evidence supporting the hypothesis that exporting fosters profitability, or, in
23
other words, that causality runs from exporting to profits. For Finland we
find virtually no evidence suggesting that Finnish export starters convert to
a different profitability path relative to continuing non-traders. However,
for the Netherlands there is some evidence suggesting that export starters
in manufacturing sectors materialize higher profits in the longer run, that
is, two to three years after foreign market entry. The results indicate that
new exporters seem to be willing to fully explore the possibilities that foreign
markets provide even at the cost of (temporarily) materializing lower profits.
In addition, the export share in total sales could increase over time, relative to the earliest years of foreign market entry, which correlates positively
with profitability as our findings suggest. An interesting avenue for further
research would be to further explore the profitability path of export starters
and investigate whether they convert to a higher profitability path in the
longer run, say, three to five years, when export skills are fully internalized
by the export starter. The data requirements tied to investigating this hypothesis are however considerable, since a sufficiently sizeable balanced panel
of export starters and continuing non-exporters over a period of at least five
to seven years would be needed.
An important note we should finally make is that it is well established that
internationalization positively affects the probability of firm survival. This
implies that the discounted value of future profits is likely to be higher for
trading firms compared to non-traders, irrespective of the insignificant premia
we find in our analysis regarding annual profits. However, unfortunately
we are unable to factor in the impact of trading on firm survival in the
relationship between exporting and profitability at this point. The would
also be an interesting line of research to further explore in the future.
24
A
Appendix
Table 14: Relative gross profit margin premia (Finland, pooled OLS, 20052010)
all
manufacturing sectors
micro
small
medium
service sectors
small
medium
large
all
micro
large
reference
reference
reference
reference
reference
0.004
(0.29)
0.018
(0.98)
-0.006
(-0.30)
0.019
(0.66)
-0.020
(-1.35)
-0.040∗∗
(-2.88)
-0.003
(-0.22)
-0.072∗∗
(-2.88)
0.005
(0.20)
-0.018
(-1.80)
trade dummies
non-trader
reference
reference
reference
reference
reference
only exports
-0.001
(-0.20)
-0.005
(-0.67)
0.000
(0.03)
0.030∗
(2.40)
.
.
only imports
0.002
(0.51)
0.003
(0.47)
0.002
(0.64)
0.000
(0.02)
0.008
(0.38)
two-way trader
0.002
(0.56)
0.006
(0.87)
0.005
(1.22)
0.003
(0.57)
0.004
(0.19)
services exporter
control variables
export share
-0.043∗∗∗
(-6.47)
-0.052∗∗∗
(-4.14)
-0.058∗∗∗
(-5.82)
-0.019
(-1.52)
0.001
(0.07)
-0.012
(-0.28)
-0.019
(-0.54)
0.045
(0.56)
-0.204
(-1.60)
0.050
(1.13)
firm size (fte, log)
-0.015∗∗∗
(-13.83)
-0.016∗∗
(-2.62)
-0.023∗∗∗
(-7.19)
-0.009
(-1.36)
-0.000
(-0.01)
0.002
(0.40)
-0.005
(-0.30)
-0.008
(-0.33)
0.036
(1.26)
0.005
(1.06)
domestic firm
reference
reference
reference
reference
reference
reference
reference
reference
reference
reference
multinational
-0.007
(-0.48)
0.015
(0.39)
-0.119∗
(-2.55)
-0.007
(-0.45)
0.026
(1.48)
-0.382
(-1.18)
-0.133
(-1.80)
-0.955
(-1.10)
0.022
(0.49)
-0.003
(-0.09)
0.075∗∗∗
(18.38)
0.080∗∗∗
(11.79)
0.074∗∗∗
(17.56)
0.057∗∗∗
(5.72)
0.029∗∗∗
(6.29)
0.172∗∗∗
(10.97)
0.153∗∗∗
(12.00)
0.209∗∗∗
(6.37)
0.116∗
(2.23)
0.010
(1.10)
57,787
0.150
24,180
0.152
25,319
0.173
6,686
0.184
1,602
0.272
62,261
0.051
31,769
0.061
23,549
0.064
5,388
0.121
1,555
0.736
labor productivity (log)
No. of observations
adj. R2
Notes: All regressions include a full set of year-sector dummies. t statistics in parentheses.
25
∗
p < 0.05,
∗∗
p < 0.01,
∗∗∗
p < 0.001
Table 15: Relative gross profit margin premia (the Netherlands, pooled
OLS, 2002-2010)
all
manufacturing sectors
micro
small
medium
large
all
wholesale and retail trading sectors
micro
small
medium
large
trade dummies
non-trader
reference
reference
reference
reference
reference
reference
reference
reference
reference
reference
only exports
-0.018∗∗∗
(-10.71)
-0.023∗∗∗
(-8.61)
-0.007∗∗
(-3.28)
-0.002
(-0.32)
-0.035
(-1.55)
-0.016∗∗∗
(-10.27)
-0.017∗∗∗
(-8.05)
-0.009∗∗∗
(-4.16)
-0.011
(-1.70)
-0.022
(-1.00)
only imports
-0.013∗∗∗
(-11.82)
-0.017∗∗∗
(-10.52)
-0.007∗∗∗
(-4.84)
-0.007
(-1.64)
0.015
(0.92)
-0.015∗∗∗
(-18.56)
-0.016∗∗∗
(-16.57)
-0.008∗∗∗
(-6.65)
-0.004
(-0.75)
-0.005
(-0.27)
two-way trader
-0.022∗∗∗
(-17.62)
-0.034∗∗∗
(-17.04)
-0.012∗∗∗
(-8.02)
-0.011∗∗
(-2.72)
0.007
(0.46)
-0.021∗∗∗
(-21.05)
-0.026∗∗∗
(-19.87)
-0.013∗∗∗
(-8.63)
-0.007
(-1.31)
-0.035∗
(-2.54)
0.001
(0.28)
-0.030∗∗∗
(-4.73)
-0.010∗
(-2.43)
0.005
(0.86)
-0.008
(-0.32)
-0.019∗∗∗
(-10.30)
-0.022∗∗∗
(-9.14)
-0.019∗∗∗
(-6.90)
-0.011
(-1.59)
0.023
(0.88)
firm size (fte, log)
-0.023∗∗∗
(-46.45)
-0.064∗∗∗
(-34.79)
-0.011∗∗∗
(-9.66)
-0.005
(-1.48)
-0.013
(-1.24)
-0.010∗∗∗
(-21.89)
-0.029∗∗∗
(-21.40)
-0.001
(-1.27)
-0.001
(-0.22)
-0.005
(-0.55)
domestically controlled
reference
reference
reference
reference
reference
reference
reference
reference
reference
reference
foreign controlled
-0.011∗∗
(-3.12)
-0.080∗∗∗
(-7.29)
-0.033∗∗∗
(-6.90)
-0.014∗∗
(-3.24)
0.001
(0.11)
-0.028∗∗∗
(-10.32)
-0.053∗∗∗
(-8.74)
-0.029∗∗∗
(-9.17)
-0.018∗∗∗
(-3.37)
-0.002
(-0.23)
labor productivity (log)
0.064∗∗∗
(74.70)
0.064∗∗∗
(57.78)
0.070∗∗∗
(49.03)
0.054∗∗∗
(18.53)
0.036∗∗∗
(4.76)
0.051∗∗∗
(72.02)
0.050∗∗∗
(58.58)
0.059∗∗∗
(47.18)
0.048∗∗∗
(10.06)
0.024∗∗
(2.94)
No. of observations
adj. R2
269,122
0.116
144,467
0.108
109,596
0.177
13,810
0.180
1,249
0.191
214,651
0.130
138,255
0.123
68,613
0.203
7,095
0.152
688
0.068
control variables
export share
Notes: All regressions include a full set of year-sector dummies. t statistics in parentheses.
∗
p < 0.05,
∗∗
p < 0.01,
∗∗∗
p < 0.001
Table 16: Relative net profit margin premia (Finland, pooled OLS, 20052010)
all
manufacturing sectors
micro
small
medium
service sectors
small
medium
large
all
micro
large
reference
reference
reference
reference
reference
-0.244
(-1.17)
-0.366
(-0.91)
-0.104∗
(-2.46)
-0.031∗∗
(-2.63)
-0.006
(-0.53)
-0.040
(-1.20)
0.044
(0.63)
-0.040∗∗∗
(-4.13)
-0.020∗∗
(-2.90)
-0.026∗∗
(-3.25)
trade dummies
non-trader
reference
reference
reference
reference
reference
only exports
-0.006
(-1.69)
-0.010
(-1.89)
-0.004
(-0.78)
0.015
(1.50)
.
.
only imports
-0.008∗∗
(-2.67)
-0.005
(-1.73)
-0.012
(-1.87)
0.000
(0.01)
0.006
(0.37)
two-way trader
-0.012∗∗∗
(-4.72)
-0.016∗∗∗
(-3.48)
-0.008∗
(-2.18)
-0.005
(-0.96)
0.007
(0.46)
services exporter
control variables
export share
-0.067∗∗
(-2.85)
-0.035∗∗∗
(-3.68)
-0.110∗
(-2.05)
-0.038∗∗∗
(-4.89)
-0.046∗∗∗
(-3.86)
0.210
(1.13)
0.118
(0.69)
-0.002
(-0.04)
-0.082∗∗∗
(-3.67)
0.017
(0.52)
firm size (fte, log)
-0.015∗∗∗
(-13.75)
-0.014∗∗∗
(-3.41)
-0.017∗∗∗
(-4.88)
-0.002
(-0.66)
0.006
(1.09)
0.030
(1.12)
0.107
(0.43)
-0.019
(-0.98)
0.021∗∗∗
(3.50)
-0.004
(-1.08)
domestic firm
reference
reference
reference
reference
reference
reference
reference
reference
reference
reference
multinational
0.001
(0.05)
-0.032
(-1.33)
-0.075
(-1.60)
-0.005
(-0.51)
0.010
(0.79)
-0.318
(-1.67)
-0.329
(-1.19)
-0.672
(-1.63)
-0.085
(-1.73)
0.015
(0.52)
0.085∗∗∗
(9.02)
0.076∗∗∗
(18.31)
0.105∗∗∗
(4.72)
0.056∗∗∗
(8.37)
0.048∗∗∗
(8.93)
0.286∗∗
(2.86)
0.386∗
(2.21)
0.180∗∗∗
(8.46)
0.078∗∗∗
(8.09)
0.035∗∗∗
(5.91)
57,962
0.097
24,278
0.282
25,402
0.071
6,680
0.379
1,602
0.528
62,704
0.001
32,022
0.008
23,687
0.583
5,429
0.975
1,566
0.984
labor productivity (log)
No. of observations
adj. R2
Notes: All regressions include a full set of year-sector dummies. t statistics in parentheses.
26
∗
p < 0.05,
∗∗
p < 0.01,
∗∗∗
p < 0.001
Table 17: Relative net profit margin premia (the Netherlands, pooled OLS,
2002-2010)
all
manufacturing sectors
micro
small
medium
large
all
wholesale and retail trading sectors
micro
small
medium
large
trade dummies
non-trader
reference
reference
reference
reference
reference
reference
reference
reference
reference
reference
only exports
-0.021∗∗∗
(-12.53)
-0.023∗∗∗
(-8.64)
-0.014∗∗∗
(-6.94)
-0.007
(-1.29)
-0.036
(-1.58)
-0.012∗∗∗
(-7.77)
-0.012∗∗∗
(-5.98)
-0.007∗∗
(-3.08)
-0.006
(-0.85)
0.009
(0.47)
only imports
-0.013∗∗∗
(-11.02)
-0.016∗∗∗
(-9.12)
-0.008∗∗∗
(-5.42)
-0.011∗
(-2.46)
0.017
(1.15)
-0.014∗∗∗
(-16.64)
-0.014∗∗∗
(-14.35)
-0.008∗∗∗
(-6.37)
-0.010∗
(-2.07)
0.005
(0.28)
two-way trader
-0.020∗∗∗
(-16.47)
-0.030∗∗∗
(-14.94)
-0.014∗∗∗
(-8.99)
-0.014∗∗∗
(-3.53)
-0.002
(-0.17)
-0.015∗∗∗
(-14.94)
-0.018∗∗∗
(-13.79)
-0.010∗∗∗
(-6.44)
-0.009
(-1.56)
-0.012
(-0.85)
0.005
(1.44)
-0.018∗∗
(-2.80)
-0.005
(-1.25)
0.004
(0.64)
0.011
(0.39)
-0.010∗∗∗
(-5.48)
-0.009∗∗∗
(-3.96)
-0.014∗∗∗
(-5.00)
-0.006
(-0.78)
-0.015
(-0.38)
firm size (fte, log)
-0.018∗∗∗
(-36.40)
-0.058∗∗∗
(-29.84)
-0.005∗∗∗
(-4.72)
-0.003
(-0.78)
-0.016
(-1.40)
-0.007∗∗∗
(-15.99)
-0.028∗∗∗
(-19.82)
0.003∗∗
(2.69)
-0.003
(-0.77)
-0.003
(-0.30)
domestically controlled
reference
reference
reference
reference
reference
reference
reference
reference
reference
reference
foreign controlled
-0.010∗∗
(-2.93)
-0.062∗∗∗
(-5.42)
-0.026∗∗∗
(-4.87)
-0.015∗∗
(-3.13)
0.007
(0.52)
-0.022∗∗∗
(-7.67)
-0.046∗∗∗
(-6.84)
-0.022∗∗∗
(-6.59)
-0.015∗∗
(-2.59)
-0.007
(-0.66)
labor productivity (log)
0.075∗∗∗
(79.62)
0.075∗∗∗
(60.60)
0.083∗∗∗
(55.10)
0.057∗∗∗
(16.96)
0.029∗∗∗
(3.66)
0.062∗∗∗
(78.14)
0.061∗∗∗
(65.11)
0.071∗∗∗
(49.17)
0.058∗∗∗
(9.94)
0.026∗∗
(2.93)
No. of observations
adj. R2
269,362
0.128
144,558
0.117
109,727
0.209
13,830
0.186
1,247
0.177
214,796
0.162
138,327
0.153
68,684
0.244
7,097
0.172
688
0.046
control variables
export share
Notes: All regressions include a full set of year-sector dummies. t statistics in parentheses.
∗
p < 0.05,
∗∗
p < 0.01,
∗∗∗
p < 0.001
Table 18: Relative return on assets premia (Finland, pooled OLS, 20052010)
all
manufacturing sectors
micro
small
medium
service sectors
small
medium
large
all
micro
large
reference
reference
reference
reference
reference
-0.036∗∗∗
(-6.58)
-0.024∗∗
(-3.13)
-0.045∗∗∗
(-5.27)
-0.042∗
(-2.13)
-0.006
(-0.16)
-0.029∗∗∗
(-5.73)
-0.015∗
(-1.97)
-0.034∗∗∗
(-4.58)
-0.014
(-0.82)
0.029
(0.86)
trade dummies
non-trader
reference
reference
reference
reference
reference
only exports
-0.020∗∗
(-3.26)
-0.024∗∗
(-2.79)
-0.023∗
(-2.42)
0.008
(0.40)
.
.
only imports
-0.004
(-1.07)
-0.006
(-1.10)
-0.007
(-1.43)
0.006
(0.45)
0.118∗
(2.42)
-0.027∗∗∗
(-6.92)
-0.033∗∗∗
(-4.38)
-0.030∗∗∗
(-5.57)
-0.008
(-0.81)
0.031
(1.17)
two-way trader
services exporter
control variables
export share
-0.065∗∗∗
(-9.15)
-0.039∗∗
(-2.60)
-0.065∗∗∗
(-6.01)
-0.074∗∗∗
(-6.11)
-0.087∗∗∗
(-4.09)
-0.084∗∗∗
(-5.87)
-0.070∗∗
(-3.18)
-0.090∗∗∗
(-4.23)
-0.129∗∗∗
(-3.51)
-0.093
(-1.55)
firm size (fte, log)
-0.020∗∗∗
(-15.23)
-0.019∗∗
(-2.64)
-0.024∗∗∗
(-6.03)
-0.009
(-1.15)
0.006
(0.78)
0.008∗∗∗
(3.85)
0.013
(1.42)
0.010
(1.39)
0.031∗
(2.19)
-0.038∗∗
(-2.65)
domestic firm
reference
reference
reference
reference
reference
reference
reference
reference
reference
reference
multinational
-0.006
(-0.36)
0.010
(0.16)
-0.072
(-1.59)
0.001
(0.07)
0.012
(0.62)
-0.056∗∗
(-2.63)
-0.118∗∗∗
(-3.59)
-0.095∗
(-2.54)
0.059
(1.40)
-0.002
(-0.05)
0.051∗∗∗
(38.48)
0.051∗∗∗
(30.77)
0.054∗∗∗
(23.49)
0.044∗∗∗
(9.85)
0.035∗∗∗
(5.31)
0.058∗∗∗
(37.05)
0.067∗∗∗
(33.05)
0.058∗∗∗
(23.37)
0.029∗∗∗
(6.66)
-0.013
(-1.91)
43,584
0.103
17,100
0.109
19,606
0.099
5,476
0.098
1,402
0.134
49,333
0.083
24,317
0.109
19,124
0.091
4,520
0.036
1,372
0.043
labor productivity (log)
No. of observations
adj. R2
Notes: All regressions include a full set of year-sector dummies. t statistics in parentheses.
27
∗
p < 0.05,
∗∗
p < 0.01,
∗∗∗
p < 0.001
Table 19: Relative return on assets premia (the Netherlands, pooled OLS,
2002-2010)
manufacturing sectors
micro
small
medium
all
large
all
wholesale and retail trading sectors
micro
small
medium
large
trade dummies
non-trader
reference
reference
reference
reference
reference
reference
reference
reference
reference
reference
only exports
-0.041∗∗∗
(-16.18)
-0.048∗∗∗
(-12.12)
-0.022∗∗∗
(-7.50)
-0.014
(-1.49)
-0.048
(-1.23)
-0.044∗∗∗
(-15.12)
-0.049∗∗∗
(-12.69)
-0.022∗∗∗
(-5.61)
-0.039∗∗∗
(-3.89)
-0.017
(-0.40)
only imports
-0.027∗∗∗
(-13.38)
-0.036∗∗∗
(-11.42)
-0.013∗∗∗
(-6.08)
-0.016∗
(-2.49)
0.002
(0.08)
-0.053∗∗∗
(-28.78)
-0.060∗∗∗
(-25.95)
-0.028∗∗∗
(-11.68)
-0.030∗∗∗
(-4.02)
0.012
(0.28)
two-way trader
-0.031∗∗∗
(-16.73)
-0.054∗∗∗
(-17.79)
-0.017∗∗∗
(-7.92)
-0.022∗∗∗
(-3.73)
0.002
(0.13)
-0.054∗∗∗
(-29.26)
-0.067∗∗∗
(-27.79)
-0.029∗∗∗
(-11.89)
-0.031∗∗∗
(-3.90)
-0.033
(-0.82)
0.013∗∗
(2.76)
-0.031∗∗∗
(-3.57)
-0.002
(-0.41)
-0.004
(-0.42)
-0.013
(-0.53)
-0.015∗∗∗
(-4.41)
-0.010∗
(-2.16)
-0.027∗∗∗
(-5.67)
-0.025∗
(-2.27)
-0.016
(-0.39)
firm size (fte, log)
-0.040∗∗∗
(-48.16)
-0.118∗∗∗
(-33.23)
-0.014∗∗∗
(-7.92)
-0.006
(-1.20)
-0.011
(-0.98)
-0.025∗∗∗
(-29.35)
-0.075∗∗∗
(-25.48)
-0.001
(-0.60)
-0.005
(-0.92)
0.020
(1.32)
domestically controlled
reference
reference
reference
reference
reference
reference
reference
reference
reference
reference
foreign controlled
0.020∗∗∗
(4.74)
-0.041∗∗∗
(-3.56)
-0.018∗∗
(-2.75)
-0.004
(-0.80)
0.023
(1.57)
0.004
(1.03)
-0.025∗∗∗
(-3.48)
-0.008
(-1.76)
-0.008
(-1.15)
-0.021
(-0.85)
labor productivity (log)
0.060∗∗∗
(54.30)
0.057∗∗∗
(38.65)
0.071∗∗∗
(39.36)
0.058∗∗∗
(15.36)
0.030∗∗∗
(5.00)
0.077∗∗∗
(74.43)
0.074∗∗∗
(58.61)
0.096∗∗∗
(51.58)
0.075∗∗∗
(15.53)
0.048∗∗
(3.05)
No. of observations
adj. R2
266,520
0.043
142,162
0.040
109,301
0.106
13,812
0.165
1,245
0.187
213,518
0.083
137,193
0.074
68,545
0.217
7,094
0.242
686
0.118
control variables
export share
Notes: All regressions include a full set of year-sector dummies. t statistics in parentheses.
∗
p < 0.05,
∗∗
p < 0.01,
∗∗∗
p < 0.001
Table 20: Relative gross profit per employee premia (Finland, pooled OLS,
2005-2010)
all
micro
manufacturing sectors
small
medium
large
all
micro
service sectors
small
medium
large
reference
reference
reference
reference
reference
652.008
(0.71)
-338.205
(-0.48)
2139.957
(1.07)
-244.550
(-0.13)
-4499.812
(-1.77)
-857.625
(-1.57)
-668.566
(-0.96)
257.273
(0.31)
-4228.134
(-1.43)
-3267.232
(-1.73)
trade dummies
non-trader
reference
reference
reference
reference
reference
only exports
-9.639
(-0.02)
194.611
(0.29)
214.599
(0.30)
-2376.020
(-1.07)
.
.
only imports
188.003
(0.53)
1135.778∗∗
(2.86)
-217.496
(-0.55)
-1547.867
(-0.53)
-12395.560
(-0.98)
two-way trader
708.465
(1.83)
1817.835∗∗
(2.91)
1591.071∗∗∗
(3.31)
-2858.974∗
(-2.29)
-1111.277
(-0.20)
services exporter
control variables
4018.462∗∗∗
(4.10)
-715.003
(-0.65)
5019.775∗∗∗
(4.69)
8288.445∗
(2.53)
2576.635
(0.37)
3648.971∗
(2.53)
2733.507
(1.87)
3224.538
(1.33)
8247.206∗
(2.46)
21237.205∗∗
(3.27)
firm size (fte, log)
432.906∗
(2.39)
-1566.388∗∗
(-3.00)
259.147
(0.57)
-1942.086
(-1.03)
-1051.762
(-0.37)
-305.566
(-1.38)
-27.886
(-0.03)
-317.916
(-0.32)
2329.623
(1.76)
798.479
(0.86)
domestic firm
reference
reference
reference
reference
reference
reference
reference
reference
reference
reference
multinational
767.285
(0.38)
7302.312
(1.81)
3652.768
(0.65)
-2142.425
(-0.76)
-1828.077
(-0.53)
23296.611
(1.76)
8276.116
(1.06)
51173.595
(1.57)
4116.487
(0.86)
3156.516
(0.59)
5250.106∗∗∗
(28.30)
5017.989∗∗∗
(32.07)
4695.334∗∗∗
(24.40)
8657.913∗∗∗
(5.21)
15681.151∗∗∗
(3.95)
5012.037∗∗∗
(18.70)
5271.404∗∗∗
(17.94)
5039.333∗∗∗
(9.71)
3747.143∗∗∗
(5.31)
2600.040∗
(2.02)
58,864
0.091
24,827
0.241
25,768
0.107
6,707
0.088
1,562
0.091
63,757
0.064
32,502
0.078
24,106
0.064
5,535
0.104
1,614
0.200
export share
labor productivity (log)
No. of observations
adj. R2
Notes: All regressions include a full set of year-sector dummies. t statistics in parentheses.
28
∗
p < 0.05,
∗∗
p < 0.01,
∗∗∗
p < 0.001
Table 21: Relative gross profit per employee premia (the Netherlands,
pooled OLS, 2002-2010)
all
micro
manufacturing sectors
small
medium
large
wholesale and retail trading sectors
micro
small
medium
all
large
trade dummies
non-trader
reference
reference
reference
reference
reference
reference
reference
reference
reference
reference
only exports
-524.512∗∗
(-2.61)
-704.049∗
(-2.28)
156.351
(0.60)
103.981
(0.13)
-7189.361∗
(-2.30)
-1424.047∗∗∗
(-5.40)
-1184.562∗∗∗
(-3.43)
-979.651∗∗
(-2.68)
-5141.640∗∗∗
(-4.06)
-7112.109
(-1.51)
only imports
166.667
(1.36)
-47.431
(-0.28)
499.606∗∗
(3.05)
19.313
(0.03)
804.498
(0.30)
-1711.211∗∗∗
(-15.58)
-1579.156∗∗∗
(-12.10)
-1366.982∗∗∗
(-7.53)
-3869.054∗∗∗
(-6.14)
-7385.014∗
(-2.10)
1087.267∗∗∗
693.861∗
1589.614∗∗∗
(7.01)
(-2.98)
(-2.25)
-181.133
(-0.74)
-2822.863∗∗∗
(2.53)
702.933
(0.33)
-479.393∗
(6.25)
386.684
(0.63)
-491.864∗∗
(-3.88)
-7088.922∗
(-2.13)
export share
5148.118∗∗∗
(8.83)
2329.825∗
(2.19)
5098.522∗∗∗
(6.27)
5698.536∗∗∗
(4.27)
-3311.235
(-0.76)
4261.300∗∗∗
(8.66)
3962.516∗∗∗
(5.93)
4299.725∗∗∗
(6.07)
4268.416∗
(2.37)
6587.649
(0.93)
firm size (fte, log)
-2413.103∗∗∗
-6289.946∗∗∗
-947.329∗∗∗
-5016.921∗∗∗
two-way trader
control variables
(-40.49)
(-35.50)
(-6.73)
-775.065
(-1.46)
445.348
(0.28)
-1734.171∗∗∗
(-23.55)
(-23.68)
-139.135
(-0.68)
-177.990
(-0.24)
-235.705
(-0.18)
reference
reference
reference
reference
reference
reference
reference
reference
reference
reference
foreign controlled
2505.602∗∗∗
(4.85)
-1646.540
(-1.12)
1731.335∗
(2.13)
1295.371
(1.58)
-1760.750
(-0.97)
-749.492
(-1.69)
-3747.731∗∗∗
(-4.60)
-1276.925∗
(-2.17)
1286.591
(1.34)
-819.089
(-0.36)
labor productivity (log)
11254.002∗∗∗
(95.97)
11425.489∗∗∗
(79.92)
11196.040∗∗∗
(54.53)
11136.507∗∗∗
(21.22)
10167.351∗∗∗
(6.58)
14700.667∗∗∗
(103.54)
14186.412∗∗∗
(86.66)
16724.897∗∗∗
(58.33)
13876.961∗∗∗
(15.90)
14980.453∗∗∗
(5.07)
269,594
0.269
145,404
0.279
109,289
0.277
13,685
0.239
1,216
0.220
212,476
0.337
137,040
0.333
67,833
0.377
6,930
0.304
673
0.257
domestically controlled
No. of observations
adj. R2
Notes: All regressions include a full set of year-sector dummies. t statistics in parentheses.
∗
p < 0.05,
29
∗∗
p < 0.01,
∗∗∗
p < 0.001
Table 22: Definition of cohorts for PSM-analysis of export starters
2002
2003
2004
2005
2006
2007
NT
proft+1
prof.grt,t+1
NT
proft+2
prof.grt+1,t+2
NT
proft+3
prof.grt+2,t+3
NT
NT∗
proft
NT
proft+1
prof.grt,t+1
NT
proft+2
prof.grt+1,t+2
NT
proft+3
prof.grt+2,t+3
NT
NT
NT∗
proft
NT
proft+1
prof.grt,t+1
NT
proft+2
prof.grt+1,t+2
NT
proft+3
prof.grt+2,t+3
NT
NT
NT∗
proft
NT
proft+1
prof.grt,t+1
NT
proft+2
prof.grt+1,t+2
NT
proft+3
prof.grt+2,t+3
NT
NT
NT∗
proft
NT
proft+1
prof.grt,t+1
NT
proft+2
prof.grt+1,t+2
NT
NT
NT∗
proft
NT
proft+1
prof.grt,t+1
NT
NT
NT∗
proft
continuing non-trader
NT
NT
NT∗
proft
NT
export starter
NT
NT EXP∗
proft
NT
2008
2009
2010
EXP
proft+1
prof.grt,t+1
EXP
proft+2
prof.grt+1,t+2
EXP
proft+3
prof.grt+2,t+3
NT
EXP∗
proft
EXP
proft+1
prof.grt,t+1
EXP
proft+2
prof.grt+1,t+2
EXP
proft+3
prof.grt+2,t+3
NT
NT
EXP∗
proft
EXP
proft+1
prof.grt,t+1
EXP
proft+2
prof.grt+1,t+2
EXP
proft+3
prof.grt+2,t+3
NT
NT
EXP∗
proft
EXP
proft+1
prof.grt,t+1
EXP
proft+2
prof.grt+1,t+2
EXP
proft+3
prof.grt+2,t+3
NT
NT
EXP∗
proft
EXP
proft+1
prof.grt,t+1
EXP
proft+2
prof.grt+1,t+2
NT
NT
EXP∗
proft
EXP
proft+1
prof.grt,t+1
NT
NT
EXP∗
proft
Notes: NT denotes non-trading, EXP denotes exporting. ∗ marks the year t of treatment. The years of measurement of the
average treatment effect on the treated (ATT) are italicized. The outcome variables employed for measurement of the ATT are
presented below the trade status in the relevant years, with proft denoting the profit level in year t and prof.grt,t+1 denoting
profit growth from year t to t+1. The sections above the dashed lines only apply to the Netherlands, the sections below the
dashed lines apply to both Finland and the Netherlands.
30
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