How do exporters react to changes in cost competitiveness?.
Date: 2015-07-23
Institutions: European Central Bank
Subjects: business policy, competitiveness, export, import, international trade, trade policy, trading operation, wage cost

WO R K I N G   PA P E R   S E R I E S
N O   1752   /   D E C E M B E R   2014

HOW DO EXPORTERS REACT TO 
CHANGES IN
COST COMPETITIVENESS?

Stefaan Decramer, Catherine Fuss and Jozef Konings

THE COMPETITIVENESS 
RESEARCH NETWORK

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CompNet

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The Competitiveness Research Network

This  paper  presents  research  conducted  within  the  Competitiveness  Research  Network  (CompNet).  The  network  is  composed  of 
economists from the European System of Central Banks (ESCB) - i.e. the 28 national central banks of the European Union (EU) and the 
European Central Bank – a number of international organisations (World Bank, OECD, EU Commission) universities and think-tanks, 
as well as a number of non-European Central Banks (Argentina and Peru) and organisations (US International Trade Commission). 

The objective of CompNet is to develop a more consistent analytical framework for assessing competitiveness, one which allows for a 
better correspondence between determinants and outcomes. 

The research is carried out in three workstreams: 1) Aggregate Measures of Competitiveness; 2) Firm Level; 3) Global Value Chains 

CompNet  is  chaired  by  Filippo  di  Mauro  (ECB).  Workstream  1  is  headed  by  Chiara  Osbat,  Giovanni  Lombardo  (both  ECB)  and 
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Acknowledgements
This paper beneﬁ ted from discussions at the FREIT 2013 conference, Ljubljana and discussions at the ECB CompNet meeting December 
2013. We thank Filip Abraham, Flora Bellone, Koen Breemersch, Jan De Loecker, Jo Van Biesebroeck, Hylke Vandenbussche and two 
anonymous  referees  of  ECB-CompNet  for  useful  suggestions  and  discussions. The  views  expressed  in  this  paper  are  those  of  the 
authors and do not necessarily reﬂ ect the views of the National Bank of Belgium.

Stefaan Decramer
University of Leuven

Catherine Fuss
NBB, Belgium and Université Libre de Bruxelles

Jozef Konings (corresponding author)
University of Leuven and University of Ljubljana; e-mail: Joep.Konings@kuleuven.be

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ISSN  
ISBN 
DOI 
EU Catalogue No   

1725-2806 (online)
978-92-899-1492-5
10.2866/773985
QB-AR-14-126-EN-N (online)

 
 
 
 
 
 
 
 
 
Abstract 

Policy-making institutions such as the European Commission, the ECB and the OECD often use unit 
labor costs as a measure of international competitiveness. The goal of this paper is to examine how well 
this measure is related to international export performance at the firm level. To this end, we use Belgian 
firm-level data for the period 1999-2010 to analyze the impact of unit labor costs on exports. We use exports 
adjusted for their import content. We find a statistically significant negative effect of unit labor costs on 
export performance of firms with an estimated elasticity of the intensive margin of exports ranging between 
-0.2 and -0.4. This result is robust to various specifications, including firm, time and sector fixed effects 
and estimation approaches. We find that this elasticity varies between sectors and between firms, with firms 
that are more labor-intensive having a higher elasticity of exports with respect to unit labor costs. The micro 
data also enable us to analyze the impact of unit labor costs on the extensive margin. Our results show that 
higher  unit  labor  costs  reduce  the  probability  of  starting  to  export  for  non-exporters  and  increase  the 
probability  of  exporters  stopping.  While  our  results  show  that  unit  labor  costs  have  an  impact  on  the 
intensive margin and extensive margin of firm-level exports, the effect is rather low, suggesting that pass-
through  of  costs  into  prices  is  limited  or  that  demand  for  exported  products  is  not  elastic.  The  latter  is 
consistent with recent trade models emphasizing that not only relative costs, but also demand factors such 
as quality and taste matter for explaining firm-level exports. 

Key words: unit labor costs, exports, competitiveness, heterogeneity 

JEL classification:  F1, F4, F16 

ECB Working Paper 1752, December 20141 
 
 
Non-technical summary 

Globalization  and  its  associated increase in international  competition  has  led  to  the  view that 

exports have become more sensitive to costs. International cost competitiveness is often measured in 

terms of unit labor costs, defined as labor cost per unit of output. This rests on the idea that increases in 

unit labor costs are passed on into higher  export prices, and consequently hurting export sales. While 

there is a clear policy concern about the evolution of unit labor costs in many European countries, there 

exists little conclusive evidence about the impact of unit labor costs on export performance. The goal of 

this paper is to examine how well this measure of unit labor costs is related to export performance at the 

firm level. In particular, we  use a confidential  Belgian  firm-level data set with detailed information  on 

costs, productivity and exports for the period 1999-2010. Taking a microeconomic perspective with these 

disaggregated data, we are able to consider various dimensions often ignored by the earlier literature. 

More precisely, we study not only the export performance of continuing exporters, but also entry and exit 

of firms into export. Further, we allow for heterogeneous effect of unit labor costs on export performance 

according to firm and sector characteristics.  

Our results show a negative relation between unit labor costs and exports at the firm level: an 

increase of unit labor costs with 10 percent, implies a drop in exports between 2 and 4 percent. We find 

that  this  elasticity  varies  between  sectors  and  firms,  notably  that  labor  intensive  firms  have  a  higher 

elasticity of exports with respect to unit labor costs. In addition,  the evidence shows that higher unit labor 

costs  decrease  the  probability  of  starting  to  export  for  non-exporters  and  increase  the  probability  of 

stopping to export for exporters. 

Our paper helps evaluating the use of unit labor cost as a competitiveness indicator. While our 

results show that unit labor costs indeed have an impact on firm-level exports, the effect is rather limited, 

suggesting that pass-through of costs into prices is limited or that demand for exported products is not 

elastic. The latter indicates that other factors such as taste and quality may at least be as important to 

incorporate in indicators of competitiveness, as suggested by the recent trade models focusing on quality 

and taste parameters. An important challenge for constructing indicators of competitiveness is therefore 

to identify proper measures for quality and taste.  

ECB Working Paper 1752, December 20142 
 
 
 
I. 

Introduction 

The  growing  imbalances  in  the  euro  area  have  triggered  a  debate  about  the  role  of  cost 
competitiveness  for  growth  and  how  far  austerity  should  go.  When  competitiveness  improves, 
countries  can  ‘grow’  out  of  the  crisis  and  hence  austerity  measures  become  less  stringent. 
Globalization  and  its  associated  increase  in  international  competition  has  led  to  the  view  that 
exports have become more sensitive to costs and hence competitiveness is often measured in terms 
of unit labor costs2, defined as the labor cost per unit of output. The focus on unit labor costs as a 
measure for competitiveness is based on the idea that increases in unit labor costs are passed on in 
the form of higher export prices, resulting in a deterioration in the balance of payments, hampering 
economic growth and increasing unemployment. The unequal evolution of unit labor costs in the 
euro area has therefore been a major concern in recent  years, or as the ECB puts it in a recent 
report3:  “Cumulative  increases  in  labor  costs  across  euro  area  countries  can  be  indicative  of 
growing imbalances and losses in competitiveness and, as such, are an important early sign of the 
need for adjustment. Relative developments in labor costs across the euro area countries, together 
with other indicators of competitiveness, have therefore to be closely monitored.”  

While there is a clear policy concern about the evolution of unit labor costs in many European 
countries,  stirred  by  close  monitoring  by  the  European  Commission,  there  exists  very  little 
conclusive evidence about the impact of unit labor costs on export performance. As early as the 
seventies, Kaldor (1978) had argued that the growth in unit labor costs to measure international 
competitiveness is at best too simplified.  In particular, he  demonstrated that countries with the 
highest growth rates in GDP tend to have high growth rates in unit labor costs. This is also known 
as the 'Kaldor paradox'4. In Figure 1, we plot the evolution of the aggregate export market share 
of Belgium and the aggregate relative unit labor costs (relative to the EU27). While we can note a 
negative correlation, it is clearly not a very strong one. For instance, from 2007 onwards it seems 
that  relative  unit  labor  costs  and  export  market  shares  have  been  moving  together.  The  simple 
correlation coefficient between the growth in RULC and the growth in export market share for the 
entire period is in fact quite weak, only -0.044. 

2 See for instance the European Competitiveness Report 2012 of the European Commission. 
3 ECB (2008), ‘Monitoring Labor Cost Developments across Euro Area Countries’, Monthly Bulletin 
4 Fagerberg (1988) analyzes this in more detail using macro data on technological competitiveness 

ECB Working Paper 1752, December 20143 
 
 
 
 
 
                                                           
Figure 1 (source: Eurostat) 

1,2

1,1

1

0,9

0,8

2000

2002

2004

2006

2008

2010

Export share Belgium in EU27 (2000 = 1)

Relative Unit Labor Cost (ULC Belgium compared to ULC EU) (2000 = 1)

This apparent paradox has also recently been documented for Spain during the great recession 
where, despite the unfavorable evolution of Spanish relative export prices, only a modest decline 
in  Spanish  exports  took  place  (Correa-Lopez  and  Domenech,  2012).  This  'disconnect'  between 
relative  costs  and  exports  has  also  been  a  widely  researched  puzzle  in  international  macro 
analyzing low exchange rate pass-through into export prices. When changes in relative costs (or 
real  exchange  rates)  only  have  a  limited  impact  on  relative  export  prices  and  hence  on  export 
quantities,  the  policy  focus  on  wage  moderation  and  convergence  of  unit  labor  costs  between 
countries seems less appropriate. What explains this low aggregate correlation and does it mean 
that the widely used measure of unit labor costs to measure competitiveness should not be used? 

Both  the  theoretical  and  empirical  work  has  stressed  the  importance  of  taking  firm-level 
heterogeneity into account. The use of micro data helps to understand the different dimensions of 
trade,  such  as  the  extensive  and  intensive  margins.  Furthermore,  it  helps  to  avoid  biases  from 
aggregation (such as “the Spanish paradox”) as explained in Altomonte et al. (2013). Recent work 
in international trade therefore makes increasing use of detailed disaggregated data to understand 
the apparent low correlation between  a number  of macro aggregates.  For instance, Amiti et al. 
(2013) used highly disaggregated firm-product data to show that the largest exporters are also the 
largest importers. This turns out to be important because when exporters are hit by an exchange 
rate  shock  in  their  destination  market,  they  typically  face  a  compensating  movement  in  their 
marginal  costs  if  they  are  importing  their  intermediate  inputs.  And  since  the  largest  exporters 
account for  most of  the  exports, they dominate the aggregate picture.  In  fact, while the largest 
exporters tend to have an exchange rate pass-through of about 50%, the smallest exporters have a 
nearly complete pass-through. In this paper, we therefore turn to disaggregated data, at the firm 

ECB Working Paper 1752, December 20144 
 
 
level, to analyze the relationship between changes in unit labor costs and firm export performance. 
It  also  enables  us  to  incorporate  the  heterogeneity  of  firms  in  the  analysis  and  to  distinguish 
between the intensive and extensive margin.    

More specifically, we use a confidential Belgian firm-level dataset with detailed information 
on  costs,  productivity  and  exports  for  the  period  1999-2010.  These  data  are  provided  by  the 
National Bank of Belgium, which collects the annual accounts of firms and merges them based on 
a unique company identifier (VAT number) to the trade data that originate from the Customs for 
non-EU  trade  and  a  compulsory  survey  on  trade  activity  for  EU  trade  (see  data  appendix). 
Furthermore, we supplement these data with confidential sales data from the VAT registry as small 
firms are not required to report sales in their company accounts.  

By using disaggregated data, we are able to better take into account the heterogeneity between 
firms  that  export.  This  is  illustrated  clearly  from  the  highly  skewed  export  distribution  that 
characterizes exporting firms in Figure 2, where we show the Lorenz curve for exports. It shows 
the relation between the cumulative fraction of exports and the cumulative fraction of the number 
of  firms  accounting  for  these  exports.  In  other  words,  we  can  see  that  20  percent  of  Belgian 
exporters account for almost 90 percent of all exports. Thus exports are concentrated in the hands 
of a small group of large exporters, which will dominate the aggregate exports, a stylized fact that 
has also been documented by Muuls and Pisu (2009) for Belgium and for other countries, e.g. by 
Bernard et al. (2007) using similar firm-level data to ours. 

Figure 2: Lorenz curve of exports (source: NBB and own calculations for the year 2004) 

e
u

l

a
v

t
r
o
p
x
e

e
v

i
t
a

l

u
m
u
C

1

8
.

6
.

4
.

2
.

0

0

.2

.4

.6

Cumulative fraction of firms

.8

1

ECB Working Paper 1752, December 20145 
 
 
 
 
But, typically, these large exporters also tend to be the largest importers of intermediate inputs, 
as pointed out by Amiti et al. (2013). Having access to imported intermediate inputs is not only a 
channel that firms can use as a hedging tool, but it can also encourage firms to start innovating and 
exporting.  Goldberg  et  al.  (2012)  show  how  firms  having  access  to  imported  inputs  start  to 
innovate  more  in  India,  while  Amiti  and  Konings  (2007)  and  Halpern  et  al.  (2011)  show  how 
having access to imported inputs enhance productivity growth. This reflects the growing role of 
international supply chains, which suggests an alternative approach to analyzing competitiveness. 
In fact, a recent  report by  the OECD  (2013)  makes  this precise point, showing that the  rise of 
global  value  chains  implies  that  the  production  process  is  dispersed  across  different  countries. 
Exports  therefore  contain  a  large  component  of  intermediate  imported  inputs.  In  small  open 
economies especially, the import content of exports reaches more than 40% of total exports on 
average.  Ignoring  the  import  content  of  exports  in  analyzing  competitiveness  may  result  in 
wrongly attributing gains in export performance of firms to improved cost competitiveness. High 
export growth may just reflect the fact that some firms import products to re-export them. Or when 
firms only add limited value to imported inputs, exports reflect mainly the value of the intermediate 
inputs. We therefore analyze net exports to capture firm-level competitiveness, although we also 
report results based on gross export numbers as a robustness check.  

Earlier  work  using  mostly  aggregate  data  found  a  weak  or  even  positive  relationship 
between relative costs or prices and exports. Only a limited number of research papers examine 
the link between unit labor costs and export competitiveness. Fagerberg (1988) uses macro data 
for Japan, the US and the UK and finds that relative unit labor costs still matter, but competition 
in technology and the ability to compete on delivery turn out to be more important. In contrast, 
Carlin et al. (2001), using disaggregated sector-level data for 15 OECD countries, find a robust 
relationship  between  relative  costs  and  exports,  with  an  elasticity  of  export  market  share  with 
respect  to  relative  unit  labor  costs  of  -0.26.  However,  they  fail  to  find  any  strong  evidence  of 
factors  going  beyond  relative  costs,  such  as  the  role  of  R&D  spending.  Correa-Lopez  and 
Domenech (2012) emphasize that the relatively modest decline in Spanish export markets despite 
the  unfavorable  evolution  of  Spanish  relative  export  prices  is  largely  due  to  firms’  strategic 
decisions,  such as  investment in human  capital,  quality upgrading  and on market and  financial 
strategies. Altomonte  et  al. (2012)  use  firm-level survey data  (EFIGE) to show how unit  labor 
costs affect the probability of being an exporter.  

In this paper, we investigate the relationship between unit labor costs and export performance 
for a small open economy, Belgium. Taking a microeconomic perspective, we are able to consider 
various dimensions often ignored by the earlier literature. More precisely, we consider both the 
intensive margin (export performance of continuing exporters) and extensive margin (entry and 
exit of firms into export) of exports. Furthermore, we allow for heterogeneous effects of unit labor 
costs on export performance according to firm and sector characteristics. We also evaluate the role 
of wages versus productivity in the impact of unit labor costs on exports. 

ECB Working Paper 1752, December 20146 
The paper is structured as follows. In Section II, we provide theoretical background, starting 
with a description of how the Melitz (2003) model illustrates the relationship between unit labor 
costs  and  firm-level  export  performance.  Section  III  describes  the  data.  Section  IV  reports  the 
results. We conclude in Section V. 

II.  Theoretical Background 

Earlier work on international trade and competitiveness focuses on the relationship between 
between  unit  labor  costs  and  export  performance  at  the  country  level.  E.g.  Farenberg  (1988) 
presents a general equilibrium model where country-level prices are determined by unit labor costs 
and  a  fixed  mark-up.  In  this  model,  lower  unit  labor  costs  increase  the  country’s  GDP,  boost 
exports and reduce imports. 

However, recent work in international trade emphasizes the importance of firm heterogeneity. 
We use the seminal paper by Melitz (2003) as a framework to illustrate the relationship between 
cost competitiveness and export performance at the firm level. We focus on the main components 
that are relevant in this context, and for further details we refer to the Melitz (2003) paper itself. 
In this model, labor is treated as a homogeneous factor of production and the wage per worker is 
equal across all firms. Therefore labor productivity drives export performance. To align the Melitz 
model with the concept of unit labor costs, we slightly modify it to allow for different wages across 
firms. Wages can be different for a number of reasons, which we do not explicitly model.  

We  follow  Melitz  (2003)  and  model  demand  as  a  representative  consumer  with  C.E.S. 

preferences over a continuum of goods, index-linked by ω: 

(cid:1) = (cid:3)(cid:4)

(cid:11)∈(cid:13)

(cid:5)((cid:7))(cid:9)(cid:10)(cid:7)

(cid:15)/(cid:9)
(cid:14)

. 

with U the utility of the representative consumer, (cid:17) the set of available goods. Because these goods 
are substitutes, (cid:18) is between 0 and 1. The corresponding sales of each good ω depend on the total 
demand in the market, R, the aggregate price level, P, and the price level of the firm p(w ): 

(cid:19)((cid:7)) = (cid:20) (cid:3)

1−(cid:25), 

(cid:21)((cid:7))
(cid:22) (cid:14)

with (cid:25) the elasticity of substitution between goods, and (cid:25)>1.  
On  the  supply  side,  firms  produce  a  single  variety  ω  and  have  labor  as  the  only  input  in  the 
production process. Labor can be expressed as a linear function of output: l = f + q/(cid:30). Firms face 
the same fixed cost of production f, but the marginal cost depends on the productivity level of the 
firm (cid:30). Firms with a high (cid:30) are able to produce more units (cid:5) with the same use of labor  . Without 
modeling the details of the labor market, we assume that firms can differ in the wage per worker 

ECB Working Paper 1752, December 20147 
 
! they face, in addition to differences in productivity. Profit maximization implies the following 
 over marginal cost: 
price-setting rule at the firm level, setting a fixed mark-up 1 ρ⁄ = σ (σ − 1)

⁄

(cid:21)((cid:30)) =

!

(cid:18)(cid:30)    . 

In this setting, !/(cid:30) represents the labor cost per unit of output, or unit labor costs. Total revenue 
of the firm therefore becomes: 

r((cid:30), !) = R (cid:3)

*+(cid:15)

(
) (cid:22)(cid:18)(cid:14)

= (cid:20)((cid:22)(cid:18))*+(cid:15) ∙ - .(cid:15)+*, 

(T1) 

with R the total sales across all products and P the price index. The firm’s revenue depends on 
various factors, but there is an inverse relation between unit labor costs and the revenues of the 
firm. This depends on the elasticity of substitution σ on the market.  

Considering  an  open  economy  implies  taking  into  account  variable  and  fixed  trade  costs. 
Omitting  further  details  of  the  model,  we  simply  state  that,  under  variable  iceberg  trade  costs, 
revenue on the foreign market (which equals export by definition) is proportional to revenue as in 
the  expression  in  equation  (T1).  So,  expression  (T1)  guides  our  analysis  for  investigating  the 
intensive margin. 

Taking the natural logarithm of (T1), we see that the elasticity of exports compared to unit 
labor costs is 1- σ according to this model. This provides us with a benchmark for the elasticities 
we find in the empirical section. More specifically, we expect an elasticity of exports to unit labor 
costs of 0 when the elasticity of substitution between varieties is perfectly inelastic (σ=1), and an 
elasticity of exports to unit labor costs of minus infinity when the elasticity of substitution between 
varieties is perfectly elastic (σ=∞). To analyze the extensive margin within this framework, we 
follow the standard Melitz (2003) assumption that exporters face a fixed export entry cost. The 
assumption is needed because of the demand structure. If there are no fixed costs of exporting, 
every active firm will export given the CES utility (this is not the case in more general approaches 
using quadratic utility as in Di Comite et al., 2014, for instance). If we assume a fixed cost /0
 per 
period of being active in the export markets, only the more productive firms will find it profitable 
to export, that is, only firms where the following holds:    

with 10
firms, measured by unit labor costs, will be able to enter and stay active on the export market. 

 profits on the export markets and (cid:19)0

10(- .) =

23(456)

7 − /0 ≥ 0, 
 revenue on the export market. Only the cost-efficient 

More recent papers have shown that demand factors are important too, especially in explaining 
the intensive margin. Baldwin and Harrigan (2011), for example, introduce quality differentiation 
in a Melitz-type model to get predictions that give a closer fit with the data. Di Comite et al. (2014) 
argue  that,  next  to  quality,  taste  is  an  important  demand  factor  to  consider  in  explaining  the 

ECB Working Paper 1752, December 20148 
 
 
 
 
 
differences  of  within-firm-product  exports  across  different  destinations.  They  introduce  both 
vertical  and  horizontal  differentiation  in  a  Melitz-Ottaviano  (2008)-type  model  but  without 
imposing  any  relationship  between  cost,  taste  and  quality.  Against  this  backdrop,  theoretical 
predictions are less clear cut on the extent to which relative unit labor costs are able to explain 
differences in relative export performance. In this respect, more empirical guidance is needed. We 
therefore  seek  to  estimate  first  the  relationship  between  unit  labor  costs  and  firm  export 
performance. Next, we analyze to what extent factors going beyond cost competitiveness matter. 
Finally,  we  also  analyze  the  role  of  unit  labor  costs  in  explaining  the  extensive  margin.  More 
specifically, we investigate the correlation of unit labor costs with entry into and exit from export 
markets, and with the “within-firm” extensive margin i.e. adding and dropping export products or 
destinations.  

III. 

 Data and summary statistics 

Our main data source is the National Bank of Belgium balance sheet database, providing a 
comprehensive panel of Belgian firms’ income statements, with detailed financial and operational 
information,  for  the  period  1999-2010.  Belgian  firms  are  legally  required  to  submit  full  or 
abbreviated company accounts, which implies that our data cover most active firms5. Since small 
firms are not required to report their sales, we supplement these data with confidential data from 
the VAT register on sales, in order to increase the number of observations in our sample. We focus 
on  manufacturing  firms  as  most  exports  and  imports  would  take  place  by  these  firms.  Some 
exporting is by firms active in the wholesale sector (distribution). They are typically intermediaries 
in  trade,  which  we  do  not  consider  in  our  analysis  as  they  do  not  actually  produce  the  goods 
themselves, so that their cost competitiveness is less relevant to explaining export performance. 
We merge these firm-level company accounts with data on exports and imports at the individual 
firm level.  

The trade data are collected through a compulsory survey for intra-EU trade and by customs 
for extra-EU trade. These data include all firms that engage in international trade above a minimum 
threshold. For extra-EU trade, this threshold is an import or export value of at least 1,000 euro, 
while for intra-EU trade the threshold is higher, total imports or exports have to be at least 250,000 
euro in a year. Since 2006, this threshold has gone up to 1,000,000 euro for exports and 400,000 
euro for imports per  year.  While the trade data  report exports and imports at the  firm-product-
destination level, we aggregate them up at the firm level since we observe unit labor costs not at 
the firm-product level, but just at the firm level. By adding the product or destination dimension, 
we would just inflate the dimension of the dataset, duplicating observations on unit labor costs of 
the same firm, which does not add additional insights.  

5 The self-employed have a simple way of reporting financial information and are not included in the data. 

ECB Working Paper 1752, December 20149 
 
    
                                                           
We follow the OECD and Eurostat in defining unit labor cost (ULC) as the total cost of labor 

per unit of output, but computed at the level of the individual firm: 

(cid:1):;<= =

>?@
A?@

(5) 

 is the total nominal employee compensation, including social security contributions, for 
where B<=
firm i at time t, and E<=
 is the deflated value added of the firm, which we use as a proxy for real 
output6. This measure of unit labor costs is equivalent to marginal costs when only one factor of 
production, labor, is used in production and the production process displays constant returns to 
scale. They are linked to export performance if increases in unit labor costs are passed on into 
higher prices, and consequently exports decline. 

To test for heterogeneity in firm export performance in response to changes in unit labor 
costs, we experiment with a number of indicators, such as the firm-level capital-labor ratio, the 
destination GDP per capita and a crisis dummy. We also make a distinction between high-tech and 
low-tech  sectors  to  capture  the  degree  of  non-price  competition.  This  measure  is  based  on  the 
Eurostat classification of high-tech/low-tech manufacturing sectors7.  

Table 1 shows summary statistics for the exporting firms in our sample and we compare them 
with manufacturing firms that never export, pooled over all years. In our analysis, we have over 
6,000 firms that export and for which we have information on labor costs, employment and value 
added8. The average manufacturing exporter employs 91 workers compared to only 9 employees 
in firms that never export. Exporters have also higher labor costs, but this is compensated by higher 
labor productivity compared to non-exporters, so that they still have slightly lower unit labor costs. 
The  fact  that  exporters  are  larger,  more  productive  and  pay  higher  wages  confirms  one  of  the 
stylized facts that has been documented in similar firm-level data for other countries. The average 
exporting  firm  exports  18  million  euro  worth  and,  when  importing,  imports  13.9  million  euro. 
About 80% of the firms in our sample that export are also importers. Furthermore, exports and 
imports are highly correlated with a correlation coefficient of 0.66. This demonstrates that most 
exporters rely on imports of intermediate inputs in their production process or that exporters simply 
re-export  imported  products,  as  shown  by  Damijan  et  al.  (2013).  Hence,  ignoring  the  import 
content of exports may lead to wrongly concluding that firms and sectors are highly competitive 
when  they  have  strong  export  growth,  while  this  may  merely  reflect  high  import  growth.  This 
suggests that measuring export competiveness as net exports, i.e. the difference between exports 
and imports, is a more sensible approach, which is what we will do in our analysis. The average 
net exporter firm has net exports which are about half of gross exports (not shown in table) and 

6 We use a 2-digit value added deflator from Belgian national accounts. 
7 We aggregate Eurostat’s definition of high technology and medium-high technology to one category, high-tech 
sectors. 
8 Only for firms that report full annual accounts we have complete information, smaller firms are not required to 
report all accounting information.  

ECB Working Paper 1752, December 201410 
     
 
 
                                                           
the growth in gross exports (0.05 when considering only net exporters) is higher than the growth 
in net exports (0.007, see table) on average. 

Table 1: summary statistics 

exporter 

# Firms 
Employment 
Labor cost per worker in euro 
Real value added per worker  
Tangible fixed assets per worker (K/L) in euro 
Unit labor cost 
Exports (X million euro) 
Importer (= 1 if imports >0) 
Imports (X million euro, importers only) 
Net exporter (=1 if net exports > 0) 
Net exports (X million euro, net exporters only) 
Growth in labor cost per worker 
Growth in  real value added per worker 
Growth in unit labor costs 
Growth in exports 
Growth in net exports 
EU orientation (=1 if EU exports in total 
exports>0.70)  
Note: Standard deviations in brackets. Averages are taken across all time periods.   

6,161 
91 (308) 
40,979 (15,565) 
83,571 (730,342) 
71,976 (1,004,659) 
0.70 (1.91) 
18.0 (119) 
0.80 (0.40) 
13.9 (108) 
0.55 (0.50) 
15.4 (72.8) 
0.03 (0.11) 
0.007 (0.27) 
0.024 (0.26) 
-0.03 (0.81) 
0.007 (0.60) 
0.64 (0.37) 

non-exporter 

16,981 
9.0 (25.1) 
32,407 (12683) 
70,886 (224,943) 
93,951 (547,496) 
0.73 (9.71) 
0 
0.15 (0.35) 
0.8 (3.4) 
0 
- 
0.03 (0.17) 
0.004 (0.32) 
0.029 (0.31) 
- 
- 
- 

To further illustrate the cross-sectional differences between exporters and non-exporters, 

we turn to a formal econometric analysis. More specifically, we run the following regression: 

log ( H<=) = (cid:18) IJ0 + log (KL(cid:21)<=) + MN + M= + O<=

, 

 stands for a dummy taking the value ‘1’ when the firm is an exporter, log (KL(cid:21)) is the 
where IJ0
natural  logarithm  of  employment,  which  we  include  to  control  for  size 9,  and   MN
 are 
respectively  sector  and  time  dummies.  The  dependent  variable log ( H<=) stands  for  the  natural 
logarithm  of  the  variable  of  interest,  i.e.  employment,  capital-labor  ratio,  labor  productivity, 
average wage and unit labor cost. The results are shown in table 2. We see that exporters are much 
larger in terms of employment (column 1), and conditional on employment, they have a higher 
capital-labor  ratio  (column  2),  a  higher  labor  productivity  (column  3),  a  higher  average  wage 
(column 4) and a lower unit labor cost (column 5).  

 and M=

9 The importance ofcontrolling for firm size, and more specifically employment size, is explained in detail in the 
appendix. 

ECB Working Paper 1752, December 201411 
 
 
                                                           
Table 2: differences between exporters and non-exporters 

(1) 
Emp 
1.694** 
(0.0195) 
No 
163385 
0.305 

(2) 
K/L 
0.373** 
(0.0179) 
Yes 
158673 
0.097 

(3) 
Q/L 
0.280** 
(0.00698) 
Yes 
163240 
0.162 

(4) 
W/L 
0.104** 
(0.00374) 
Yes 
163251 
0.343 

(5) 
ULC 
-0.221** 
(0.00638) 
Yes 
164754 
0.209 

IJ0

Size control 
Observations 
R2 
Standard errors in parentheses 
+ p < 0.10, * p < 0.05, ** p < 0.01 

While unit labor costs may be high and increasing, suggesting a deterioration in firm-level 
competitiveness, it may be triggered by either excessive nominal wage growth or insufficient labor 
productivity growth, or a combination of both. To illustrate this, we decompose unit labor costs 
into its sub-components, the nominal labor cost per worker (i.e. the total wage bill per worker) and 
output per worker or labor productivity: 

(cid:1):;<= =

>?@
A?@

=

>?@ P?@⁄
A?@ P?@⁄

.  

(6) 

Figure  3  shows  the  aggregate  evolution  of  ULC  for  our  dataset,  and  the  evolution  of  its  two 
components. The aggregation is done by simply dividing the total wage bill summed across all 
firms by the total value added summed across all firms in our dataset for each year. We used the 
value for the year 1999 as the reference to construct the index. The labor cost per worker is rising 
almost linearly, with an increase of about 36% between 1999 to 2010. As can be noted from table 
1, the growth in nominal labor costs in the average firm is also 3 percent per year, which reflects 
the  aggregate  evolution  in  nominal  labor  costs.  In  figure  3,  we  can  see  that  aggregate  labor 
productivity also rose, but not at the same pace as aggregate labor costs. Up to 2004, growth in 
labor productivity was below  growth in nominal labor costs, but it reversed between 2005 and 
2007. Since the crisis years, labor productivity growth has been lower again than growth in labor 
costs, and it was in fact negative for 2008 and 2009. As a result, aggregate unit labor costs in our 
sample have been relatively stable apart from the crisis years. However, the aggregate picture in 
figure 3 hides a substantial amount of heterogeneity between firms.  

ECB Working Paper 1752, December 201412 
 
 
 
 
 
 
 
 
Figure 3: Aggregate evolution of unit labor cost, labor productivity and wages per worker 
Source: own calculations based on NBB data 

Unit labor costs, wages and labor productivity

x
e
d
n

i

4

.

1

3

.

1

2

.

1

1

.

1

1

9

.

8

.

2000

2005

Year

2010

wage per worker
unit labor cost

labor productivity

To illustrate this, figure 4 distinguishes between non-exporters (left) and exporters (right) 
when  calculating  the  aggregate  evolution  of  unit  labor  costs,  wage  per  worker  and  labor 
productivity. We see that the pattern is quite different for labor productivity, while the average 
wage evolution is roughly similar, although there is some difference during the last two years. Also 
the evolution of unit labor costs is different, with non-exporters experiencing a rise  in  the first 
years, then a relatively stable pattern until the rise in the crisis years 2009 and 2010, while exporters 
experience a rise, but then a decline from 2004 to 2006, and then again a substantial rise in 2008 
and  2009  to  go  down  again  in  2010.  The  distinction  between  non-exporters  and  exporters  is 
relevant for the analysis, as the changes in non-exporters’ unit labor costs will not have an impact 
on the intensive margin of continuing exporters, but could have an indirect effect on the export 
performance of sectors or Belgium as a whole through the extensive margin of entering and exiting 
the export markets. Therefore we study the extensive margin as well in our results section.  

ECB Working Paper 1752, December 201413 
 
 
Figure 4: Aggregate evolution of unit labor cost, labor productivity and wages per worker, 
distinguishing between non-exporters (left) and exports (right) 

Source: own calculations based on NBB data 

IV.  Results 

In this section, we start by analyzing the baseline relationship between the intensive margin 
of net exports and unit labor costs at the firm level, using various estimation approaches. Next, we 
exploit differences between sectors and the role of firm heterogeneity and finally we tune in on the 
relationship between the extensive margin of exports and unit labor costs. 

IV.1 Baseline results 

Following the discussion in section II, we start by estimating a simple relationship between 
firm-level (net) export values and unit labor costs. The basic export equation we seek to estimate 
is derived from equation (T1) and given by: 

QR<= = S ∙ Q- .<= + MN= + O<=

(7) 

where all variables are in logs. We use a first-differenced model to control for unobserved firm-
 represents the log of net exports in euros of firm i at time t, and - .<=
fixed effects. The variable R<=
represents the log unit labor costs of firm i at time t. To control for sector specific business cycles 
and shocks, we include sector-year fixed effects MN=
. Finally, O<= is a white noise error term. We 
start by estimating this basic equation using OLS in table 3, while in table 4 we report the same 
estimates, but using system GMM to account for potential endogeneity of unit labor costs.  We 

ECB Working Paper 1752, December 201414 
   
 
 
 
 
 
 
 
 
 
 
 
 
 
consistently cluster the standard errors at the firm level throughout the paper, but our results are 
robust to alternative clustering, such as clustering at the sector level or at the sector-year level10. 

In the first column of table 3, we estimate equation (1) including a full set of sector times year 
effects, while in the second column we do the same but include sector and year effects separately. 
Both  specifications  yield  very  similar  results  with  an  estimated  elasticity  of  net  exports  with 
respect to unit labor costs of close to -0.3. In the third column, we include as an additional control 
variable the change in capital stock, taking into account the fact that capital investment may drive 
exports and at the same time boost the capital input share, which would cause a drop in unit labor 
costs. This may take place when firms decide to substitute labor for capital when labor costs are 
rising. But we can note that the estimated elasticity remains statistically significant with a very 
similar point estimate of -0.28.  

To assess whether it is mainly nominal wage costs or changes in productivity that drive the 
results, we decompose in the third and fourth column unit labor costs in the nominal wage cost per 
worker and output per worker. The results in column (3) show that firms that are more productive 
in terms of output per worker export more (an elasticity of 0.30), while the estimated coefficient 
on nominal wages per worker is negative, but small and not statistically significant different from 
zero. This suggests that the variation in unit labor costs firms face is mainly driven by changes in 
labor productivity. As shown in table 1, there is actuallymuch more variation in labor productivity 
than in wages. Given that the wage formation process in Belgium is centralized and a large part of 
the variation in wages is driven by institutional factors, such as collective agreements at sector 
level11 or automatic wage indexation, the variation of wage costs at the firm level is most likely 
going to be small.   

A concern with the results based on OLS in table 3 is potential endogeneity of unit labor costs 
and in particular of labor productivity. Our specifications control for firm-unobserved effects (by 
taking first differences) and for sector-specific business cycles and demand shocks by including 
sector-time fixed effects. However, one could still argue that there is an endogeneity issue to the 
extent that wages and output are jointly determined by the firm. Rent-sharing between the firm and 
the workers would create a downward bias (in absolute value) of the elasticity we are estimating 
if exports are positively correlated with profits. There could also simply be reverse causality when 
there is ‘learning from exporting’, albeit in advanced countries like Belgium, it is less likely that 
this is going to be a dominant factor12. If there is an impact of exporting on productivity we would 

10 Taking for example the baseline specification presented in the third column in table 2, we find a standard error for 
ΔULC of 0.0208 when clustering at the firm level, 0.0260 when clustering at the sector (NACE 2-digit) level and 
0.0220 when clustering at the sector-year level. This might suggest that the standard errors are larger when clustering 
at the sector level, but this is not the case for all specifications. We also checked the robustness for the long differences 
(table 4) and the heterogeneity table (table 8, presented further on in this paper), and find that all coefficients keep 
their significance level when clustering at the sector level instead of the firm level. When clustering at the sector-year 
level, standard errors are consistently lower across the different specifications.  
11 E.g., see Lopez and Sissoko (2013). 
12 Pisu (2008) finds no support for the learning-by-exporting hypothesis for Belgium. 

ECB Working Paper 1752, December 201415 
                                                           
expect this is also reflected in nominal wages and hence unit labor costs (that is, nominal wages 
adjusted for real labor productivity) should be unaffected. By contrast, if wages and labor are rigid 
and reacting less to changes in output, this could lead to an upward bias (in absolute value) of the 
elasticity.  

Table 3: OLS results, dependent variable Δ Net export value 

Δ ULC 

Δ K 

Δ Q/L 

Δ W/L 

(1) 

(2) 

(3) 

-0.292** 
(0.0210) 
- 
- 
- 

-0.281** 
(0.0206) 
- 
- 
- 

-0.283** 
(0.0208) 
0.0920** 
(0.0134) 

- 

- 

- 

Sector × year effects 
Year effects 
Sector effects 
Observations 
R2 
Standard errors clustered at the firm level in parentheses. All variables are in logs. 
+ p < 0.10, * p < 0.05, ** p < 0.01 

No 
Yes 
Yes 
23207 
0.023 

No 
Yes 
Yes 
23009 
0.026 

Yes 
No 
No 
23207 
0.039 

(4) 

- 

0.0922** 
(0.0134) 
0.313** 
(0.0213) 
-0.0348 
(0.0512) 
Yes 
No 
No 
22987 
0.044 

(5) 

- 

0.0911** 
(0.0134) 
0.301** 
(0.0208) 
-0.0155 
(0.0515) 
No 
Yes 
Yes 
22987 
0.029 

We  attempt  to  mitigate  the  potential  endogeneity  issues  in  a  number  of  ways,  apart  from 

controlling for fixed effects. First, we estimate the relation described in equation in levels, i.e. 

xVW = α< +  β ∙ ulcVW + μ]W + εVW

(8) 

with System GMM, using lags 2 and 3 of unit labor cost as instruments in the difference equation 
and the first lag of Q- . in the level equation13. The results are shown in table 4, where we show 
various specifications, starting in column (1) with just including year fixed effects, in column (2) 
we include a full set of sector times year effects, columns (3) – (4) further include the capital stock 
as an extra control. For the first columns, the Hansen p test and the second order correlation test 
do  not  reject  the  model,  which  suggests  the  model  is  well  specified.  Note  that  the  number  of 
observations  reported  for  the  System  GMM  specification  cannot  be  directly  compared  to  the 
number of observations in our OLS first-difference baseline specification in table 3.14  

13 These are the standard instruments for endogenous regressors, see Roodman (2009). For additional background on 
Difference and System GMM, see also Arellano and Bond (1991), Arellano and Bover (1995) and Blundell and Bond 
(1998). 
14 The fact that the number of observations in table 4 is different from the number of observations in table 3 is not 
driven  by  the use of different samples. The sample  used in both  estimations  is the same. However,  we follow the 
reporting standard for  System  GMM,  which is  reporting the  total  number  of observations  available in levels.  The 

ECB Working Paper 1752, December 201416 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
                                                           
The results in table 4 show a point estimate of the elasticity of exports with respect to unit labor 
costs  of  approximately  -0.40.  When  we  also  control  for  the  change  in  capital  stock,  assumed 
exogenous, the elasticity remains very similar, with a point estimate ranging between -0.43 and -
0.53 in columns (3) and (4). When we compare the point estimates of the OLS specifications in 
table 3 and the GMM system specifications, we can see that on average the latter yields a point 
estimate of the unit labor cost elasticity that is 10 to 25 percentage point above that obtained from 
the OLS specification, but this difference is limited taking into account the standard errors. We 
will therefore use OLS in the remainder of our analysis. 

Table 4: System GMM Estimation, dependent variable: Net export value 

ULC 

K 

(1) 
-0.401** 
(0.150) 
- 

(2) 
-0.434** 
(0.144) 
- 

(3) 
-0.434** 
(0.123) 
0.737** 
(0.012) 
Yes 
No 
0.149 
0.038 
29,965 

(4) 
-0.536** 
(0.119) 
0.748** 
(0.0128) 
Yes 
Yes 
0.087 
0.05 
29,965 

Year effects 
Sector effects 
Hansen J test p-value 
AR 2 p-value 
Observations 
Standard errors clustered at the firm level in parentheses. All variables are in logs. Instruments for ULC include 
lagged values of the ULC from t-2 to t-3 (difference equation) and the difference between t-2 and t-1 (level 
equation).  + p < 0.10, * p < 0.05, ** p < 0.01 

Yes 
Yes 
0.297 
0.281 
29,965 

Yes 
No 
0.478 
0.265 
29,965 

So far, our estimates have been based on one-year differences. Of course, firms may need time 
to adjust and short-run rigidities may result in biased estimates of the long-run elasticity of net 
exports with respect to unit labor costs. We therefore report the same set of results using five-year-
long differences instead of one-year differences. The results are shown in table 5. Not surprisingly, 
the elasticity increases and falls in between -0.35 and -0.40. In column (5), we lag unit labor costs 
with one period as an additional robustness check, but the results hardly change.  

number of observations actually used is substantially lower, as the instruments are not available for all observations. 
The  number  of  observations  in  our  first-difference  OLS  specification  in  table  3  is  lower  than  the  number  of 
observations in levels because differencing leads to a reduction of the sample size.   

ECB Working Paper 1752, December 201417 
 
 
 
 
                                                           
Table 5: Dependent variable Δ5 Net export value - long differences (5 years). 

(1) 

(2) 

(3) 

(4) 

(5) 

Δ5 ULC 

Δ5 K 

-0.391** 
(0.0364) 

-0.402** 
(0.038) 

-0.381** 
(0.0369) 

Sector × year 
Sector effects   
Year effects 
Observations 
R² 
Standard errors clustered at the firm level in parentheses. All variables are in logs. Specification (5) uses unit labor 
costs lagged once. + p < 0.10, * p < 0.05, ** p < 0.01 

No 
No 
No 
11,744 
0.023 

No 
Yes 
Yes 
11,744 
0.049 

Yes 
No 
No 
11,744 
0.06 

-0.356** 
(0.0346) 
0.205** 
(0.0178) 
No 
Yes 
Yes 
11,625 
0.074 

-0.353** 
(0.0409) 
0.210** 
(0.0192) 
No 
Yes 
Yes 
9,411 
0.079 

Finally,  we  check  whether  the  sensitivity  of  exports  with  respect  to  unit  labor  costs  is 
different when other export measures are used. First, we check the results when gross exports are 
used,  rather  than  net  exports,  as  the  dependent  variable;  i.e.  using  exports  without  subtracting 
imports.  The  results  are  reported  in  table  6a,  where  we  give  both  one-year  and  five-year 
differences. It is worth noting that we still obtain a negative and statistically significant effect of 
unit  labor  costs  on  export  performance,  however,  the  point  estimates  are  about  10  percentage 
points lower compared to the specifications in which we use net exports. 

Table 6a: Dependent variable Δ(5) Gross  export value 

Δ ULC 

Δ K 

Δ5 ULC 

Δ5 K 

(1) 

(2) 

-0.201** 
(0.0183) 

- 

- 

-0.206** 
(0.0183) 
0.0985** 
(0.0117) 
- 

- 

(3) 

- 

- 

-0.285** 
(0.0345) 

Sector × Year effects 
Observations 
R² 
Standard errors clustered at the firm level in parentheses. All variables are in logs. + p < 0.10, * p < 0.05, ** p < 0.01 

yes 
43,589 
0.029 

yes 
43,111 
0.032 

yes 
22,395 
0.042 

As a second robustness check, we use value-added exports as the dependent variable, see 
table 6b. Gross exports will not exhibit a strong link with unit labor costs if the cost of the exporting 
firm is small relative to the total cost of the exported product. This is the case if the firm makes 

(4) 

- 

- 

-0.272** 
(0.0336) 
0.264** 
(0.019) 
yes 
22,125 
0.064 

ECB Working Paper 1752, December 201418 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
heavy  use  of  intermediate  inputs.  Using  net  exports  as  the  dependent  variable,  defined  as  the 
difference of exports and imports, only mitigates this to the extent that the intermediate inputs are 
imported  by  the  firm.  If  the  firm  sources  its  intermediate  inputs  on  the  domestic  market,  there 
might  still  be  a  weak  link  between  a  value-added-based  measure  such  as  unit  labor  costs. 
Therefore, we  go one step further  and use value-added exports as a dependent variable,  which 
proxies  exports  net  of  the  intermediate  inputs  used  to  produce  the  exported  products.  An 
approximation  of  the  value-added  exports  is  obtained  by  subtracting  the  share  of  exports  in 
intermediate  inputs 15  from  the  gross  exports.  We  again  report  both  one-year  and  five-year 
differences. As before, we still obtain a negative and statistically significant effect of unit labor 
costs on export performance. The point estimates are 10 to 15 points higher in absolute value than 
the original specification with net exports. 

Moreover, going from the main specification to the robustness checks, the coefficients change in 
a  way  that  makes  sense  intuitively.  If  we  take  gross  exports  as  an  independent  variable,  the 
estimated  coefficient  becomes  lower  in  absolute  value.  A  part  of  the  gross  exports  of  a  firm 
potentially rely heavily, or even entirely as shown in Damijan et al. (2013), on imports. An increase 
in unit labor costs will not have any impact on this part of gross exports, but only the part in which 
the firm uses its workers. Therefore, we expect the elasticity of gross exports to be lower than for 
net exports. Turning to value-added exports, we see that the coefficient increases in absolute value 
compared to using net exports as the independent variable. Net exports are potentially partly driven 
by  domestically-sourced  inputs,  and  can  therefore  be  expected  to  suffer  less  from  firm-level 
increases in unit labor costs than value-added exports. So, a higher elasticity (in absolute value) 
for value-added exports is in line with our expectations.  

Table 6b: Dependent variable Δ(5) Value-added export value 

Δ ULC 

Δ K 

Δ5 ULC 

Δ5 K 

(1) 
-0.430** 
(0.0249) 

- 

- 

(2) 
-0.437** 
(0.0249) 
0.120** 
(0.0142) 
- 

- 

(3) 
- 

- 

-0.454** 
(0.0464) 

(4) 
- 

- 

-0.444** 
(0.0438) 
0.269** 
(0.0214) 

Sector × year effects 
Observations 
R2 
Standard errors clustered at the firm level in parentheses. All variables are in logs.+ p < 0.10, * p < 0.05, ** p < 0.01 

17605 
0.048 

34237 
0.028 

17448 
0.071 

34520 
0.026 

15 Value-added exports are thus defined as gross exports minus the intermediate inputs used for these exports. We only 
observe  inputs  at  the  firm  level  and  hence  do  not  observe  the inputs  corresponding  to the  exports.  Therefore,  we 
approximate the input share of exports by the share of exports in sales multiplied by the total intermediate inputs.  

ECB Working Paper 1752, December 201419 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
                                                           
The analysis shows that unit labor costs have an appreciable impact on export performance, 
but the elasticity is still  rather low.  Linking it with the  Melitz  (2003)- based theoretical  model 
presented in section II, an elasticity of exports with regards to unit labor costs of -0.2 to -0.4 implies 
an elasticity of substitution σ between varieties of 1.2 to 1.4, which is not that far from a perfectly 
inelastic elasticity of substitution (σ=1).  

IV.2 Heterogeneity in the sensitivity of exports with respect to unit labor costs 

While the above results focus on the average effect of unit labor costs on net exports, there 
may be quite a lot of heterogeneity in the responsiveness of firms with respect to changes in unit 
labor costs, depending on the product market or sector they operate in. As discussed in section II, 
recent models in international trade emphasize that, apart from relative costs, demand factors, such 
as quality and taste differences, may also be important in explaining the export performance of 
firms. Hence, sectors that are more R&D-intense may generate a different response to increases in 
unit labor costs as their product demand depends more on the degree of innovation and quality. 
We therefore estimate the elasticity of net exports with respect to unit labor costs for each two-
digit NACE sector separately, shown in table 7. The elasticity of net exports with respect to unit 
labor costs is estimated to be negative in all sectors, but its magnitude ranges between -0.084 (and 
not statistically significant) in ‘electrical equipment’ and-0.742 in ‘paper and paper products’. It is 
not  surprising  to  find  differences  across  sectors  and  we  would  expect  these  to  be  related  to 
differences in the capital labor ratio, the type of technology used or the export orientation of the 
sector,  which  reflects  different  demand  patterns  (e.g.  high-  versus  low-income  countries). 
Similarly, we may expect some sectors tobe more vulnerable to demand shocks than others. With 
the financial and economic crisis, export markets collapsed and in some product areas more so 
than in others.  

ECB Working Paper 1752, December 201420 
 
 
 
Table 7: Elasticity of net exports with regards to unit labor costs,  
according to specification (1), at the sector level. 

Sector (NACE2-digit code) 
Food products (10) 
Textiles (13) 
Wearing apparel (14) 
Wood and wood products (16) 
Paper and paper products (17) 
Printing and reproduction recorded media (18) 
Chemicals (20) 
Basic pharmaceutical products (21) 
Rubber and Plastic (22) 
Non-metallic mineral products (23) 
Basic metals (24) 
Fabricated metal products (25) 
Computer and electronic products (26) 
Electrical equipment (27) 
Machinery and equipment (28) 
Motor vehicles (29) 
Furniture (31) 

Δulc 
-0.225** 
-0.313** 
-0.465** 
-0.158+ 
-0.742** 
-0.302** 
-0.374** 
-0.373** 
-0.178** 
-0.275** 
-0.270** 
-0.285** 
-0.276** 
-0.084 
-0.452** 
-0.224** 
-0.278** 

s.e. 
0.049 
0.049 
0.110 
0.085 
0.146 
0.145 
0.058 
0.113 
0.081 
0.088 
0.092 
0.084 
0.127 
0.107 
0.083 
0.107 
0.127 

Obs 
3,385 
2,548 
658 
653 
601 
667 
1,980 
324 
1,907 
1,154 
679 
2,498 
831 
693 
2,221 
561 
910 

Standard errors clustered at the firm level in parentheses. All regressions include time fixed effects and have Δ K as 
control variable. The sectors beverages (11) tobacco products (12), leather products (15), coke and refined products 
(19) and other transport equipment (30), are not displayed because of the low number of observations for these 
sectors.  + p < 0.10, * p < 0.05, ** p < 0.01 

To illustrate to which extent the elasticities in table 7 are statistically significantly different 
from each other, we show a graphical representation of the point estimates with the corresponding 
95% confidence interval in figure 5. The overlap of the confidence intervals gives an indication of 
whether the point estimates are significantly different from each other.For example, food products 
(10)  and  textiles  (13)  have  confidence  intervals  that  overlap  substantially.  The  difference  in 
elasticities  is  0.088  in  absolute  value  with  a  standard  error  of  0.069  and  thus  not  statistically 
significant  at  the  conventional  significance  levels  (with  a  p-value  of  approximately  20%).  The 
difference in elasticity between the sectors wearing apparel (14) and wood and wood products (16) 
is statistically significant: the difference is 0.307 with a standard error of 0.139 and a p-value of 
2.8%. The graph shows that the confidence intervals of the coefficients of these sectors only have 
limited overlap.  

ECB Working Paper 1752, December 201421 
 
 
 
Figure 5: Illustration of the 95% confidence intervals for the elasticities in table 7. 

To further explore the heterogeneity, we carry out additional analysis to see to what extent the 
export elasticity with respect to unit labor costs varies over time and across a number of firm and 
sector characteristics that capture different demand and supply shocks. The results are presented 
in table 8. We focus on the specification using one-year differences, but the results for five-year 
differences are qualitatively the same. The first column of table 8 interacts unit labor costs with a 
crisis dummy equal to 1 for the years 2009 and 201016. We include year-fixed effects and sector-
fixed effects separately. Note that the interaction between unit labor costs and this crisis dummy 
is positive, but statistically not different from zero. In other words, the crisis did not have an effect 
on the sensitivity of (net) exports to changes in unit labor costs. In contrast, the direct impact of 
the crisis on net exports for the average firm has been strong and negative. The cumulative direct 
impact of the years 2009 and 2010 was estimated at -0.23 (not reported in the table), which means 
that exports dropped by 23% for the average firm in 2009 and 2010. In the second column, we 
check whether firms that export to high-income countries have a different elasticity. To this end, 
we  define  the  firm-level  destination  GDP  per  capita  as  a  gross-export-weighted  average  of  the 
GDP per capita of its different destination countries and interact it with the change in unit labor 
costs.  Arguably,  if  firms  export  to  high-income  countries,  cost  competiveness  may  be  less 

16 We also experimented with defining this dummy from 2008 onwards, but the results remained the same. 

ECB Working Paper 1752, December 201422 
 
 
                                                           
important, as other aspects related to non-price competition, such as quality and reliability, may 
matter more17. We find the expected positive coefficient, but it is not statistically significant.  

In column (3), we explore to what extent non-price competition is relevant in high tech sectors, 
that typically would be able to innovate more. High-tech sectors are defined on the basis of the 
Eurostat classification of R&D-intensive manufacturing sectors. We consider sectors as high-tech 
when they are ranked according to Eurostat as either high-tech and medium-high tech18. However, 
we find no statistically significant effect of high-tech sectors. This is somewhat surprising as we 
would expect them to be able to innovate more and because non-price competition is more relevant 
in these sectors. Nonetheless, a similar result for R&D-intensive sectors was found in Carlin et al. 
(2001) using OECD sector-level data. Of course, R&D intensity is measured in a rather crude way 
at the 2-digit NACE level, while typically R&D tends to be concentrated among a few large firms. 
Firm-level data on R&D and innovation would be required, which we do not have at our disposal.  

In column (4), we test whether labor-intensive firms are more sensitive to changes in unit labor 
costs by interacting unit labor costs with the capital-labor ratio. We find that labor-intensive sectors 
have a much higher elasticity of net  exports with respect to unit labor costs relative to capital-
intensive firms.  

Finally, in column (5), we put all specifications together to check whether all these effects still 
hold, which is the case. It is clear from the results in tables 6 and 7 that an average estimate of the 
elasticity of net exports with respect to unit labor costs is not reflecting the full dimensions of firm 
responses  to  shocks  and  that,  depending  on  a  number  of  firm  and  sector  characteristics,  firm 
exports react differently to changes in unit labor costs, giving support to recent models covering 
both  cost  heterogeneity  and  demand  heterogeneity  as  in  Melitz  and  Ottaviano  (2008)  and  Di 
Comite et al. (2014).   

We also experimented with other sources of heterogeneity not reported here. We analyzed to 
what extent the export sensitivity with respect to unit labor cost depends on whether exports go to 
the EU (Internal Market effect) or not. To check if multinational groups behave differently, we 
included an interaction with the firm’s multinational status, but also did not find any statistically 
robust relationship. We also interacted the change in unit labor costs with firm size (proxied by 
log sales or employment). However, no statistically robust relationship was found. These results 
are presented in appendix 3. 

17 On a related issue, Martin and Mayneris (2014) study high-end variety exporters, defined as firms selling expensive 
varieties of a product, these varieties having specific attributes such as reputation, branding or quality that make them 
appealing despite their higher price. They find that French high-end exports are more sensitive to the average income 
of the destination country, but less sensitive to distance. This suggests that quality is more important relative to price 
(or costs) for high income countries.  
18 If we just restrict it to the very high-tech sectors, the results remain the same. 

ECB Working Paper 1752, December 201423 
 
 
                                                           
Table 8: Heterogeneity of elasticity of net exports with regards to unit labor costs over time 
and across firm and sector characteristics 

Δ ULCit 

Δ ULCit × crisist 

Δ ULCit × ln GDP per capitait-1 

Δ ULCit × High-Techs 

Δ ULCit × ln capital-labor ratioit-1 

Δ Kit 

(2) 
-0.849+ 
(0.480) 

(3) 
-0.271** 
(0.0245) 

(4) 
-0.758** 
(0.199) 

(1) 
-0.291** 
(0.0229) 
0.0394 
(0.0506) 

0.0538 
(0.0467) 

-0.0338 
(0.0452) 

(5) 
-1.280* 
(0.517) 
0.0423 
(0.0548) 
0.0505 
(0.0481) 
-0.0257 
(0.0472) 
0.0438* 
(0.0186) 
0.105** 
(0.0135) 
Yes 
22380 
0.030 

0.0433* 
(0.0186) 
0.105** 
(0.0136) 
Yes 
22393 
0.029 

Year & sector dummies 
Observations 
R2 
Standard errors clustered at the firm level in parentheses. All variables that are interacted with unit labor costs are 
also included separately in the regressions, but not reported. + p < 0.10, * p < 0.05, ** p < 0.01 

0.0918** 
(0.0134) 
Yes 
23009 
0.026 

0.0973** 
(0.0135) 
Yes 
22484 
0.029 

0.0923** 
(0.0134) 
Yes 
23009 
0.026 

IV.3 Extensive margin 

So  far,  we  have  only  focused  on  the  intensive  margin  of  exports,  i.e.  how  export  sales 
increase or decrease with changing unit labor costs. But when the fixed costs of entering export 
markets are high, unit labor costs, reflecting in part productivity, may be even more important for 
starting to export. As theoretically shown by Melitz (2003), firms self-select into export markets 
when they are more productive. So, we would expect that firms with higher unit labor costs will 
be less likely to start exporting if they are not yet exporting and more likely to stop exporting when 
already exporting. We analyze the relationship between entry into export markets and unit labor 
costs by identifying all firms that start to export in a particular year, while not exporting the year 
before. Our control group consists of all other manufacturing firms that never export. The first 
three  columns  in  table  9  reports  various  specifications  of  a  probit  model  for  entry  into  export 
markets. Note that we report the marginal effect evaluated at the means of the regressors rather 
than the probit coefficients as the latter do not have an economic interpretation. In the first column, 
we  simply  include  lagged  unit  labor  costs,  and  the  standard  year  and  sector  control  dummies. 
Contrary to our expectations, we find a statistically significant positive relation between unit labor 
costs and firm entry into export markets. However, when controlling for firm size, through log 
employment19, we find the expected negative coefficient (see the second column). The estimated 

19 The importance ofcontrolling for firm size, and more specifically employment size, is explained in detail in the 
appendix. 

ECB Working Paper 1752, December 201424 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
                                                           
effects  are  quite  low:  a  decline  in  the  ULC  from  the  75th  percentile  in  our  sample  to  the  25th 
percentile, increases the probability of becoming an exporter with approximately 1.7 percentage 
points. When going from the 10th to the 90th percentile, the increase is 3.7 percentage points. In 
the third column, we report a specification where we separately include nominal wages and labor 
productivity as is done in a number of papers that analyze the extensive margin (e.g. Bernard et 
al.,  2006).  They  indicate  that  firms  entering  export  markets  have  both  a  higher  level  of  labor 
productivity  and  higher  nominal  wages.  This  is  consistent  with  findings  in  the  literature.  For 
instance,  Bernard  et  al.  (2006)  report  a  positive  coefficient  on  both  the  wage  and  on  labor 
productivity. The positive coefficient on labor productivity reflects better firms self-selecting into 
export markets. The positive coefficient on the wage is usually interpreted as an indicator of labor 
force quality, reflected by higher nominal wages paid to workers with high human capital. The last 
three columns of table 9 show the results for firms that exit the export markets. We compare firms 
that withdraw from the export markets, while still exporting the year before, with firms that keep 
on exporting as a control group. Column (4) shows a statistically insignificant positive relation 
between unit labor costs and exit. This coefficient becomes much larger and statistically significant 
when controlling for employment, as shown in column (5). The magnitude is larger than for the 
entry analysis, but still somewhat low: an increase of unit labor costs from the 25th to the 75th 
percentile raises the probability of exit by 4 percentage points, from the 10th to the 90th percentile 
of  8.1  percentage  points.  The  final  column  shows  that  this  is  mainly  driven  by  lower  labor 
productivity and that the coefficient on wage is not statistically significant.  

Table 9: Extensive margin – exit and entry of firms 

ln ULC 

ln Employment 

ln Labor prod. 

ln Av. Wage 

(1) 
Entry 
0.00967** 
(0.0175) 

(2) 
Entry 
-0.0305** 
(0.00273) 

(3) 
Entry 

(4) 
Exit 
0.00231 
(0.006545
) 

(5) 
Exit 
0. 0680** 
(0.00771) 

-0.0707** 
(0.00231) 

0.0351** 
(0.00130) 

0.0319** 
(0.00125) 
0.0305** 
(0.00279) 
0.0137** 
(0.00484) 
Yes 
Yes 

(6) 
Exit 

-0.0635** 
(0.00231) 
-0. 0666** 
(0.00744) 
-0.0101 
(0.0118) 
Yes 
Yes 

Yes 
Yes 

Yes 
Yes 

Yes 
Yes 

Year dummies 
Sector 
dummies 
Observations 
Pseudo R2 
Log likelihood 
Standard errors clustered at the firm level in parentheses. The dependent variable is a dummy that indicates 
whether the firm started exporting. All regressors are lagged with one period. All specifications are probit 
estimations. We report the marginal effect  evaluated at the means of the regressors rather than the probit 
estimation coefficients.  + p < 0.10, * p < 0.05, ** p < 0.01 

59306 
0.118 
-12203 

59888 
0.125 
-12247 

29942 
0.066 
-10875 

60989 
0.044 
-13551 

29892 
0.254 
-8645 

Yes 
Yes 

29892 
0.264 
-8535 

ECB Working Paper 1752, December 201425 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
The disaggregated data enable us to study the ‘within-firm extensive margin’ as well, i.e. the 
impact of unit labor costs on adding or dropping products, destinations and product-destination 
combinations. We present the results in table 10. In the first column, we run a probit regression on 
a dummy taking on the value ‘1’ if a firm increases its number of export destinations compared to 
the previous year, and zero otherwise. In column 2, we use the reverse: the dependent variable 
dummy for destinations dropped takes on the value ‘1’ if the firm reduces its number of export 
destinations, and zero otherwise. We find that firms with higher unit labor costs are less likely to 
expand the number of export destinations (column 1) and more  likely to  reduce  the number of 
export  destinations  (column  2).  The  next  two  columns  show  the  same  analysis  for  exported 
products:  firms  with  higher  unit  labor  costs  are  less  likely  to  increase  the  number  of  exported 
products (column 3), and more likely to cut the number of exported products (column 4). The last 
two columns show the results for unique export destination-product combinations. In line with the 
previous results, we see that firms with higher unit labor costs are less likely to boost the number 
of export destination-product combinations (column (5)), and more likely to reduce the number of 
export destination-product combinations (column (6)).  

So, we can summarize the results for the extensive margin as follows: a higher unit labor cost 
reduces the probability of entering the export markets and increases the probability of exit from 
the export markets when controlling for firm size. Also, firms with higher unit labor costs are less 
likely  to  add  export  destinations,  export  products  and  destination-product  combinations.  The 
effects are statistically significant but rather small.  

Table 10: Extensive margin – adding/dropping of destinations, products and 

destination-product combinations 

ln ULC 

ln Employment 

(1) 
Dest. 
added 
-0.0627** 
(0.00721) 
0.0392** 
(0.00199) 
Yes 
Yes 

(2) 
Dest. 
dropped 
0.0303** 
(0.00714) 
0.0266** 
(0.00179) 
Yes 
Yes 

(3) 
Prod. 
added 
-0.0306** 
(0.00716) 
0.0360** 
(0.00191) 
Yes 
Yes 

(4) 
Prod. 
dropped 
0.0150* 
(0.00649) 
0.0251** 
(0.00181) 
Yes 
Yes 

(5) 
D-P added 

-0.0628** 
(0.00741) 
0.0341** 
(0.00204) 
Yes 
Yes 

(6) 
D-P 
dropped 
0.0380** 
(0.00682) 
0.0147** 
(0.00189) 
Yes 
Yes 

Year dummies 
Sector 
dummies 
Observations 
Pseudo R2 
Log likelihood 
Standard errors clustered at the firm level in parentheses. The dependent variable is a dummy that indicates 
whether the firm started exporting. All regressors are lagged with one period. All specifications are probit 
estimations. We report the marginal effect  evaluated at the means of the regressors rather than the probit 
estimation coefficients. + p < 0.10, * p < 0.05, ** p < 0.01 

34048 
0.011 
-21634 

34048 
0.013 
-22493 

34048 
0.007 
-22500 

34048 
0.017 
-22322 

34048 
0.013 
-23130 

34048 
0.006 
-22970 

ECB Working Paper 1752, December 201426 
 
 
 
 
 
V.  Conclusion  

Unit  labor  costs  have  been  a  widely  used  measure  for  assessing  the  competitiveness  of 
countries.  Rising  unit  labor  costs  are  usually  seen  as  a  threat  to  export  market  performance. 
However,  very  little  empirical  work  has  looked  into  the  impact  of  unit  labor  costs  on  export 
performance. This paper has tried to fill this gap by analyzing the relationship between unit labor 
costs and exports at the firm level.  

We  argue  first  that  using  micro  data  is  more  appropriate  as  there  is  a  lot  of  heterogeneity 
between firms not only in terms of productivity and hence unit labor costs, but also in terms of 
their  export  market  performance.  Furthermore,  we  analyze  net  exports  of  firms,  i.e.  exports 
adjusted for their import content, for which firm-level data seem more appropriate. 

We find that the elasticity of exports with regard to unit labor costs varies between -0.29 and -
0.40. But this elasticity varies between sectors and firms. In particular, we find that more labor-
intensive firms are more sensitive to changes in unit labor costs than firms that use more capital 
and export mainly to the EU market. The financial and economic crisis affected exports, but the 
elasticity of exports with respect to unit labor costs did not change. Finally, we show that changes 
in  unit  labor  costs  also  have  only  a  statistically  significant  impact  on  the  extensive  margin  of 
exports.  

Our results are relevant for policy-makers in understanding the role of cost competitiveness in 
export performance. The paper helps to evaluate the use of unit labor costs as a competitiveness 
indicator.  While  our  results  show  that  unit  labor  costs  have  an  impact  on  the  intensive  and 
extensive margin of firm-level exports, the impact is rather low. This suggests that pass-through 
of costs into prices is low or that demand is fairly inelastic with regard to prices. The latter finding 
indicates that other factors such as taste and quality may be just as important to incorporate into 
indicators of competitiveness, as suggested by recent trade models focusing on quality and taste 
parameters.  A  major  challenge  for  constructing  indicators  of  competitiveness  is  therefore  to 
identify proper measures for quality and taste. Also, the finding that the elasticity of exports with 
regard to unit labor costs is larger for labor intensive firms suggests that cost competitiveness is 
more important for these firms.  

ECB Working Paper 1752, December 201427 
 
 
 
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ECB Working Paper 1752, December 201429 
 
 
Appendix 1: Data description  

Reporting trade data 

Extra-EU data are taken from the customs data and intra-state survey data available at the NBB. 
Trade data are collected of all transactions with a value higher than 1,000 euro or a weight over 
1,000  kg.  Following  a  broader  use  of  electronic  reporting  producers  from  2006  onwards,  very 
small transactions are now reported while this was not the case before.  

The thresholds are more binding for intra-EU trade. From 1998 to 2005, firms had to report their 
export and import flows if these were more than 250,000 euro per year. From 2006 onwards, the 
threshold was raised to 1,000,000 euro for exports and 400,000 euros for imports.  

Firm data 

The  trade  data  are  merged  with  the  company  accounts  of  firms  using  a  VAT  number.  All 
incorporated firms in Belgium are required to submit full or abbreviated annual accounts to the 
National Bank of Belgium. Since small firms are not required to report sales, we supplement the 
firm-level data with confidential data on sales from the VAT registry. 

Data-cleaning 

The changes in unit labor costs, exports, net exports, capital, average wage, labor productivity and 
materials over sales ratio that are smaller than the first percentile of the distribution or larger than 
the 99th percentile of the distribution are dropped. For the differences between exporters and non-
exporters  in  table  2,  we  also  dropped  the  observations  in  levels  that  were  lower  than  the  first 
percentile or higher than the 99th percentile of the dependent variable.  

Appendix 2: Measurement of employment for micro firms  

When analyzing the differences between exporters and non-exporters, it is important to control for 
the fact that micro-firms seem to be exceptional. This is illustrated in table 11. We regress different 
variables of interest, i.e. labor productivity, average wage, unit labor costs and capital-labor ratio 
on five size dummies I_`abc, taking the value of one when the number of FTEs is respectively 
one or lower, strictly larger than one but smaller than or equal to two, …, strictly larger than four 
but smaller than or equal to five. The smallest firms are more productive, have a lower wage, lower 
unit labor costs and a higher capital-labor ratio. This is remarkable, as the literature generally finds 
that  productivity  and  capital  intensity  increase  with  firm  size.  We  find  the  contrary,  as  again 
confirmed in table 12 where we regress the four dependent variables on log employment. However, 

ECB Working Paper 1752, December 201430 
 
 
 
interestingly, the relation returns to “normal” when we exclude the firms with strictly more than 
five FTEs. This is shown in table 13. For this sub-set of firms, productivity, wages and capital 
intensity do in fact increase with firm size.  

The main explanation we see is that the owner of the firm is not always reported as an employee 
of the firm for micro firms, even if active in the firm20. This would explain why labor productivity 
and the capital labor ratio is so high for these small firms. An alternative explanation for the high 
labor productivity is that the marginal product of an extra employee diminishes with an increasing 
number  of  employees.  Irrespective  of  the  reason  why  micro  firms  are  more  productive,  this  is 
potentially problematic when comparing exporters and non-exporters, as the non-exporters are on 
average much smaller and contain a much higher fraction of these micro firms. Hence, we need to 
control for this in our analysis. Therefore, we include log employment as a control to take this into 
account when analyzing the differences between exporters and non-exporters and for our extensive 
margin analysis. Adding more detailed controls, e.g. employment dummies for the smallest firms, 
yields qualitatively the same results. 

Table 11: Premia for micro firms 

(1) 
Q/L 
0.302** 
(0.00951) 

0.0269** 
(0.00874) 

-0.0586** 
(0.00860) 

-0.0783** 
(0.00860) 

-0.0826** 
(0.00871) 
163240 
0.160 

(2) 
W/L 
-0.227** 
(0.00528) 

-0.215** 
(0.00509) 

-0.198** 
(0.00513) 

-0.177** 
(0.00516) 

-0.149** 
(0.00515) 
163251 
0.277 

(3) 
ULC 
-0.840** 
(0.0116) 

-0.266** 
(0.00756) 

-0.149** 
(0.00715) 

-0.102** 
(0.00669) 

-0.0747** 
(0.00702) 
168379 
0.252 

(4) 
K/L 
0.812** 
(0.0235) 

0.377** 
(0.0235) 

0.196** 
(0.0233) 

0.132** 
(0.0231) 

0.0761** 
(0.0241) 
158673 
0.100 

I_`ab(cid:15) 

I_`abd 

I_`abe 

I_`abf 

I_`abg 

Observations 
R2 
Standard errors in parentheses 
+ p < 0.10, * p < 0.05, ** p < 0.01 

20 The owner is at least partly paid through the profits of the firm. Some owners choose to be an employee of their 
firm, e.g. for tax reasons (if they pay themselves a low wage, the tax rate on their wage is lower than the corporate 
taxes), but not all owners do this. We see for instance many firms reporting zero employment in their accounting 
statements. 

ECB Working Paper 1752, December 201431 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
                                                           
Table 12: Relation with firm size 

(1) 
Q/L 
-0.0168** 
(0.00225) 
163240 
0.124 

(2) 
W/L 
0.0811** 
(0.00104) 
163251 
0.330 

(3) 
ULC 
0.126** 
(0.00224) 
164754 
0.184 

(4) 
K/L 
-0.130** 
(0.00510) 
158673 
0.085 

Log employment 

Observations 
R2 
Standard errors in parentheses 
+ p < 0.10, * p < 0.05, ** p < 0.01 

Table 13: Relation with firm size for firms with more than five FTEs 

(1) 
Q/L 
0.0787** 
(0.00339) 
92272 
0.240 

(2) 
W/L 
0.0963** 
(0.00177) 
91849 
0.420 

(3) 
ULC 
0.0197** 
(0.00257) 
92374 
0.111 

(4) 
K/L 
0.0235** 
(0.00812) 
90678 
0.111 

Log employment 

Observations 
R2 
Standard errors in parentheses 
+ p < 0.10, * p < 0.05, ** p < 0.01 

Appendix 3: Additional heterogeneity results 

In  this  section,  we  present  the  additional  heterogeneity  results  mentioned  in  section  IV.2.  The 
results  are  shown  in  table  14.  The  first  column  shows  the  interaction  with  the  EU-orientation 
dummy defined as in the summary statistics, taking the value one if the export value of the firm’s 
exports  to  EU  destinations  exceeds  70%  of  the  total  exports  and  zero  otherwise.  The  effect  is 
positive  and  statistically  significant.  However,  this  effect  is  not  robust.  The  coefficient  is  not 
statistically significant when defining the EU-orientation dummy slightly differently, e.g. using a 
threshold of 60% (coefficient drops to 0.073 with a p-value of 18%) or 80% (coefficient drops to 
0.047 with a p-value of 29%). In addition, when using gross exports as dependent variable, the 
coefficient  even  switches  sign.  So  we  do  not  find  a  robust  effect  for  the  interaction  with  EU 
orientation. The second column shows the result for an interaction with a multinational dummy, 
taking the value one if the firm is a MNE and zero otherwise. The coefficient is close to zero and 
not  statistically  significant.  Columns  3  and  4  show  firm  size  interaction,  with  respectively 
employment and sales as a proxy for firm size. Here too, we do not find any effect. 

ECB Working Paper 1752, December 201432 
 
 
 
 
 
 
 
 
 
 
 
Table 14: Heterogeneity of elasticity of net exports with regards to unit labor costs – 
additional results 
(2) 
-0.284** 
(0.0238) 

(3) 
-0.280** 
(0.0521) 

(4) 
-0.546* 
(0.217) 

Δ ULCit 

(1) 
-0.366** 
(0.0427) 
0.0961* 
(0.0488) 

Δ ULCit × EUit-1 

Δ ULCit × MNEit-1 

Δ ULCit × log Empit-1 

Δ ULCit × log Salesit-1 

0.0119 
(0.0460) 

-0.00599 
(0.0130) 

Δ Kit 

0.0913** 
(0.0134) 
Observations 
22927 
R2 
0.026 
Standard errors clustered at the firm level in parentheses. All variables that are interacted with unit labor costs are 
also included separately in the regressions, but not reported. + p < 0.10, * p < 0.05, ** p < 0.01 

0.0964** 
(0.0135) 
22482 
0.029 

0.0976** 
(0.0135) 
22497 
0.029 

0.0154 
(0.0132) 
0.0971** 
(0.0135) 
22491 
0.029 

ECB Working Paper 1752, December 201433