Título artículo / Títol article:
Fragmentation and parts and components trade in the
Western Balkan countries
Autores / Autors
Bojan Shimbov, Maite Alguacil, Celestino Suárez
Revista:
Post-Communist Economies
Versión / Versió:
Versión Pre-print
Cita bibliográfica / Cita
bibliogràfica (ISO 690):
SHIMBOV, Bojan; ALGUACIL, Maite; SUÁREZ,
Celestino. Fragmentation and parts and components
trade in the Western Balkan countries. PostCommunist Economies, 2013, vol. 25, no 3, p. 371391
url Repositori UJI:
http://hdl.handle.net/10234/114802
Fragmentation and parts and components trade in
the Western Balkan countries
Bojan Shimbov*, Maite Alguacil† and Celestino Suárez‡§
February 2013
Abstract
As a consequence of the increasing globalization and integration of the world’s
markets, there has been an intensive process of international fragmentation of
the production over the last few decades. This phenomenon whereby previously
integrated productive activities are segmented and internationally spread is
reflected in the rapid increase in parts and components trade, growing at higher
rates than final goods trade. In this process, the Western Balkan countries
(WBC) have not been an exception. With their recent integration into the global
markets, the WBC have witnessed growth in parts and components trade that
has even exceeded the world average. This paper examines the determinants of
the trade that stems from the international fragmentation of production in the
WBC. Using a panel data set of disaggregated bilateral trade flows, we estimate
gravity equations for the period 2000-2009. Our findings support the hypothesis
drawn from the theory of fragmentation that trade in parts and components is
motivated by labor cost differences and by geographical and proximity reasons.
The relevance of additional service link costs, as well as the influence of
institutional similarity and infrastructure quality or political-economic agreements
is also confirmed by our empirical research.
Key words: fragmentation, trade in parts and components, Western Balkan
countries, gravity model
JEL Classification: F10, F14, F15
*
The World Bank and the University Jaume I of Castellón (Institute of International Economics).
University Jaume I of Castellón (Department of Economics and Institute of International
Economics). E-mail address: alguacil@uji.es.
‡
University Jaume I of Castellón (Department of Economics and Institute of International
Economics). E-mail address: celes@uji.es.
†
§
The views and conclusions in this paper express the personal standing of the authors and not
necessarily the official views of their respective institutions.
1
Acknowledgements
The authors would like to thank the helpful comments received from the
participants at the 1st Meeting on International Economics (University Jaume I of
Castellón, Spain, 20/21 September 2012). They are also grateful for the financial
support from the Project P21/08 of the National plan for Research and
Development by the Ministry of Science and Innovation of the Spanish
Government as well as the Pla de Promoció de la Investigació by Fundació
Caixa Castelló-Bancaixa (P1-1A2010-05).
2
1. Introduction
Is the label “Made in …” on your computer telling the whole truth? The majority of
manufactured products that we use on a daily basis are not made entirely in the
country where they are finally assembled or sold. Most probably, some of the
parts and components are provided by foreign firms. This process may go even
deeper. A part or component from a particular country, used to assemble the final
product, might already be composed of inputs from other countries that are used
indirectly in the production of the final product. This is how international
fragmentation of the production process emerges and, as a result, the creation of
International Production Networks (IPN).
As shown by Jones et al. (2005), the rapid growth of parts and components trade
is a natural consequence of this phenomenon, where a final good is the result of
a production process that takes place in different locations. International
fragmentation of production is mainly associated with the activities of
Multinational Companies (MNC). This occurs when different stages of production
take place in subsidiaries located in different countries, thus leading to the
creation of intra-firm trade (Venables, 1999). However, this process is not
confined to the activities of a MNC, but may also occur through arm’s-length
transactions (Venables, 1999).
The pattern of trade that emerges from international fragmentation differs
depending on the reasons that drive the delocalization of the production process.
As Deardorff (1998) mentioned, fragmentation of production will only occur when
the benefits of this process that come from the location advantages of
internationalization exceed the coordination and transportation costs of
integrated production. As indicated by Jones and Kierzkowski (1990), the
fragmentation process involving countries with different levels of development
and income will be due to location advantages that stem from different factor
endowments, such as lower wages and the availability of raw materials.
Conversely, in the most advanced economies with similar incomes (mostly
2
Western European countries, the US, Canada and Japan), we would expect
trade in differentiated products to be driven by imperfect competition and variety
preferences. According to Krugman (1980) and Krugman and Helpman (1985), in
this case, trade in goods will be mainly horizontal and will not be characterized by
comparative advantages, but rather by income levels, economies of scale and
the number of varieties produced and consumed. Thus, in the former case firms
will be mainly efficiency-seeking and oriented towards reducing production costs,
while in the latter they will be serving local market demand. Consequently,
researching the nature of parts and components trade will allow us to shed some
light on the causes and consequences of the international fragmentation of
production.
During the last decade, many studies have empirically analyzed the phenomenon
of the international fragmentation of production, focusing on East Asia, the EU
and the US. It is worth highlighting the work by Athukorola and Yamashita (2006)
and Kimura et al. (2007) for East Asia; Baldone et al. (2001), Egger and Egger
(2005) and Kaminski and Ng (2005) for EU; and Görg (2000), Swenson (2005)
and Clark (2006) for the US. Studies like Yeats (2001) or Jones et al. (2005)
analyze the phenomenon on a more global basis, covering countries from all
three regions. A common outcome of this literature is that trade in intermediate
goods is expanding more rapidly than conventional final-goods trade, as a result
of the increasing disagglomeration of production. By exploiting the advantages of
favorable policy settings for international production and low service-link costs,
as well as inter country wage differentials, companies benefit from the
international fragmentation of the production process.
In this phenomenon, the Western Balkan countries (WBC), comprising Albania,
Bosnia and Herzegovina, Croatia, Macedonia, Montenegro and Serbia, are no
exception. The recent economic modernization and international opening up of
the WBC, as well as the spectacular increase in their trade in parts and
components over the last decade makes this region an interesting case to
examine.
3
(Insert Figure 1 here)
As can be seen in Figure 1, annual growth in parts and components trade in the
WBC is well above world growth over the last decade (except for the years 2000
and 2009). Average growth in parts and components imports and exports over
the period 2000-2010 in the WBC was more than two and a half times higher
than the respective world growth rate. Although there has been a decrease in the
last two years due to the collapse in trade following the financial crisis, the WBC
have recovered quite quickly. In 2010, WBC growth is only slightly negative,
compared to the significantly negative growth rate at world level.
Using disaggregated trade data
1
, this paper examines the nature and
determinants of bilateral trade in parts and components in the WBC. Following
the empirical literature2, parts and components trade is employed as an indicator
of fragmentation between the WBC and their most important trading partners.
The sample period extends from 2000 to 2009 and responds to the availability of
data for the whole country sample. This study considers factors that may
stimulate or deter trade in parts and components as well as country-specific
effects. In order to do so, a gravity panel data model is estimated. To the best of
our knowledge, there has been no previous attempt to empirically test what
determines international fragmentation in the WBC.
The remainder of the paper is structured as follows. In the next section we
present some stylized facts. In Section 3 we analyze the theoretical background
referring to the international fragmentation of the production process. Some
empirical evidence is shown at the end of the section. The methodological
framework and the different explanatory variables used are presented in Section
4. The following section presents and explains the empirical results and the final
section concludes.
1
See the Appendix for a greater detail of the used data in this work.
Most empirical research uses bilateral trade in parts and components as an indicator of
fragmentation. See, for example, Kimura at al. (2007), Kaminski and Ng (2005) and Athukorola
and Yamashita (2006).
2
4
2. Stylized facts
Until the mid-1990s, due to political instability and war conflicts, the WBC had
been beyond the direct reach of foreign firms. By the end of the decade, they had
all opened up to foreign investment with the exception of Serbia and Montenegro,
which opened up after the war in Kosovo in 1999 (and once former president
Slobodan Miloshevic had been overthrown). One key issue in this external
opening was the aspiration to join the EU. Stabilization and Association
Agreements (SAA) were subsequently signed with all WBC, which initiated the
long accession process that should eventually result in EU membership.3 This
integration process gives the WBC the opportunity to participate more actively in
the IPN.
Following the fall of the former Soviet Union and the events that followed in
Eastern European countries, the WBC entered a process of economic transition
to replace their former planned economic systems with market economies.
Reform programs pursued aims such as liberalization, stabilization and
privatization.
4
In order to converge to the ‘acquis communautaire’, this
harmonization process has expanded to areas such as market liberalization (like
telecommunications and financial systems), registering property, starting up a
business, protecting investors or enforcing contracts. All these measures
promote a business-friendly environment and minimal disruption in transportation
and communication between production segments as a necessary condition to
participate in the international division of labor and trade.
3
Albania submitted its application for EU membership in April 2009 and is currently a potential
candidate; Bosnia and Herzegovina is also considered a potential candidate country, but formal
application has not yet been submitted; Croatia is set to join the EU in July 2013, and the formal
signing of the acceptance process was carried out at the EU summit in December 2011;
Macedonia was granted candidate country status for EU membership in 2005, but negotiations
with the EU have not yet begun due to the unresolved “name” issue with Greece; Montenegro
started negotiations with the EU in June 2012; finally, Serbia was granted candidate country
status at the last EU summit in March 2012.
4
Barriers to trade including non-tariff barriers were removed and customs systems and legal
practices were aligned with those in the EU. The trade and transport facilitation program for South
Eastern Europe helped customs reforms and improved coordination between border control
agencies, as well as eliminating bottlenecks at border crossings in the region.
5
(Insert Table 1 here)
The above mentioned institutional preconditions combined with the availability of
competitive overall cost structure (labor, land and utilities cheaper than new EU
member countries) and geographical proximity to the EU, make the WBC
attractive for both efficiency-seeking and market-seeking MNC. As a result of this
process, foreign investment in these countries began to increase considerably.
As can be seen in Table 1, Foreign Direct Investment (FDI) in each WBC
displays a significant increase over the last decade, until 2008. A decline is
witnessed in 2009 and 2010 due to the current financial crisis.
(Insert Table 2 here)
The implication of this process has been a significant increase in parts and
components trade, as can be observed in Figure 1 in the previous section. This
increase is even larger than the one experienced in final goods trade. Table 2
compares the imports and exports of final machinery and transport equipment
and miscellaneous manufactured articles (hereafter machinery goods) along with
imports and exports of parts and components of the same groups.5 As can be
seen, world trade in parts and components (imports and exports) increased by
52% and 46% for the period 2000-2009, respectively. Western Balkan countries
not only achieved faster growth in imports and exports of machinery final goods
(growing at 192% and 183%, respectively), but also recorded even more intense
growth in parts and components trade. Parts and components trade increased by
257% and 343% (in imports and exports, respectively) during the same period,
which is more than double the growth rate of this type of trade at world level.
Furthermore, the increase in WBC trade in parts and components is far greater
than the increase in the other two regions in Europe. Compared to the EU-15, the
increase is more than sevenfold, while for the EU-10, the difference is above 30
5
The coverage of the parts and components included in the analysis is presented in the code list
in Appendix.
6
percentage points in the case of imports and above 90 points in the case of
exports.
However, this trade is not evenly distributed across countries. Bilateral trade is
mainly concentrated in only a few economic areas. The EU is the main trading
partner, accounting for more than 70% of all imports and exports. Within the EU
itself, the EU-15 countries (mainly Germany and Italy) are by far the most
important partners. In 2000, they accounted for 67% of all machinery parts and
components imports. However, that figure had dropped to 58% by 2009 due to
the increase in the share of EU-10 and East Asia (mainly China). The situation
on the export side has changed significantly in favor of trade with EU countries
from 75% in 2000 to 83% in 2009).
These stylized facts reveal not only the increasing relevance of trade in
intermediate goods in the WBC, but also the potential change in its geographical
pattern. In order to understand the above changes, it is important to ascertain
what drives the decision of firms when they choose to locate part of their
production in the WBC. Discovering the nature of the IPN in these countries will
help us to determine not only the pattern of trade in parts and components, but
also the potential impact of this process on economic performance within this
region. In order to explore this issue further, some theoretical aspects related to
the international fragmentation of the production process are presented in next
section.
3. Theoretical background of the fragmentation theory
It is a well-known fact that international trade does not only occur when each
partner country is specialized in products from different industries, as explained
by traditional comparative advantage theories (Ricardian model and HeckscherOhlin models). Countries may produce different types of products from the same
industry, which gives rise to intra-industry trade (IIT).
7
The concept of intra-industry trade was first introduced by Grubel and Lloyd
(1971, 1975). The understanding of this type of trade was further formalized in
theoretical terms by Krugman (1980) and Krugman and Helpman (1985), who
provide seminal contributions along the lines of Dixit and Stiglitz (1977).
According to these models, trade flows between industrialized countries should
not be characterized by comparative advantages. Conversely, the exchange of
homogeneous goods (horizontal IIT) is driven by imperfect competition and
variety preferences.
However, intra-industry trade in intermediate goods is not fully explained by
these initial models of horizontal IIT. The specialization pattern of trade in
intermediate goods seems to be more appropriately explained by the literature on
vertical IIT and the international fragmentation of the production process. 6 As
stated by Jones et al. (2002), international fragmentation or the splitting-up of an
initially integrated production process into two or more production segments that
are located in different countries, will result in vertical IIT. In this sense, while the
traditional theory of trade does not fully explain why horizontal IIT takes place, it
does justify vertical specialization and hence the international fragmentation of
production. The first general framework to analyze fragmentation was introduced
by Jones and Kierzkowski (1990). For these authors, the fragmentation of the
production process into several stages located in different countries allows firms
to select locations that are better suited in terms of factor endowments or
productivities. This would imply, on the one hand, that the most labor-intensive
stages of the production process are located in the most labor-abundant (lower
wage) countries. On the other hand, as the different stages of the production
process might require different labor skills, some countries’ labor skills might be
more appropriate to one stage than others (Ricardian productivity differences).7
However, the delocalization of the production process needs to be coordinated
and linked, which will entail service link costs such as transportation,
6
Vertical IIT is defined as the simultaneous exporting and importing of products in the same
industry, but at a different stage of production.
7
See, for example, Arndt (1997), Deardorff (2001a), or Arndt and Kierzkowski (2001).
8
communication and other coordination activities. Due to the fact that the
increasing output of the different production stages would only slightly increase
total service link costs, the larger the size of the firm and the market, the more
cost-efficient the fragmentation would be. Therefore, with service-link costs the
scale matters. In this sense, the ideas of the new trade theory and new economic
geography, concerning increasing returns to scale are also contemplated by the
fragmentation literature. Indeed, fragmentation will occur if each production stage
is more closely matched to its factor intensities and factor productivities in order
to offset the increase in service link costs. As Jones and Kierzkowski (1990)
conclude, fragmentation can lower total production costs only at the expense of
higher service link requirements.8
The international fragmentation of production therefore allows a more in-depth
specialization to take place within a single industry. On the one hand, a country
that does not have a comparative advantage in each stage of the production
process will be able to specialize in the assembly of a final good. On the other
hand, a country that does not have a comparative advantage in the production of
a final good will be able to produce at least some parts of that good. Both
processes will eventually increase trade in intermediate goods (Deardorff 1998
and 2001a).
4. Related research
Many empirical works have analyzed the determinants of the international
fragmentation of production. These studies differ in terms of the countries
analyzed, the methodologies and data employed and/or the results. Different
authors even employ dissimilar terms and measures to basically describe the
same phenomenon. 9 The strictest definition of this process entails the wellknown outward processing trade. That is, in this case the home-country firm
8
Other important contributions to the theory of fragmentation can be found in Arndt (1997), Arndt
and Kierzkowski (2001), Jones and Kierzkowski (2001b) and Deardorff (2001a).
9
Such as slicing up the value chain (Krugman 1995), outsourcing (Feenstra and Hanson 1997),
disintegration of production (Feenstra 1998), intra-product specialization (Arndt 1997), vertical
specialization (Hummels et al. 2001), or fragmentation (Jones and Kierzkowski 1990; Deardorff
2001a).
9
exports intermediate goods for further processing in a foreign country, after which
the goods are re-imported by the home-country firm. A broader definition of
fragmentation measures this process through volumes of trade flows in
intermediate goods or components (Baldone et al. 2001, Yeats, 2001, Athukorola
and Yamashita ,2006 and Kimura et al., 2007).
The focus of most of these studies has been on the three main economic regions
in the world: the US, the EU and East Asia. International fragmentation of the
production process by US firms is, for instance, studied by Swenson (2005) and
Clark (2006). The first study analyzes the cross-country pattern of US
outsourcing activities between 1980 and 2000. It explains how outsourcing is
affected by cost changes in different host countries. The study finds that US
outsourcing activities will increase as these costs fall or when a competitor
country’s costs rise. Clark (2006) investigates the determinants that influence US
firms to engage in vertical specialization. This research shows that the main
reason for US firms to engage in fragmentation is to counter a comparative
disadvantage in home production. For this author, the factors that influence the
selection of new locations include market size, proximity to foreign countries,
political freedom, degree of exchange rate distortion and labor force availability
and quality.
Studies that analyze the fragmentation process in Europe include the papers by
Egger and Egger (2005) and Kaminski and Ng (2005). Egger and Egger (2005)
use data on the bilateral outward and inward processing exports and imports of
the EU-12 economies. The authors find that the EU’s outward processing trade is
to a relatively large extent determined in line with standard Heckscher-Ohlin
arguments. Furthermore, they argue that for outward processing trade,
infrastructure variables (such as the telephone and road networks or the
electricity supply in the partner country) are also relevant. Kaminski and Ng
(2005) analyze the case of the new EU member countries (EU-10) by
investigating whether these countries have become part of the production and
10
distribution networks, concluding that they had been integrated into the global
networks.
Athukorala and Yamashita (2006) and Kimura et al. (2007) study the international
fragmentation of production in East Asia through the estimation of gravity
equations. They find not only that parts and components trade is expanding more
rapidly than final goods trade in East Asia, but also that the degree of
dependence on this form of international specialization is proportionately larger in
East Asia than in North America or Western Europe. This seems to be the result
of the relatively more favorable policy setting for international production in the
region (agglomeration benefits and wage differentials), which is in line with the
basic fragmentation literature. Comparing East Asia to Western Europe, Kimura
et al. (2007) conclude that the fragmentation theory is well suited to explaining
the mechanics of international production and distribution networks in East Asia,
while the traditional horizontal product differentiation model better explains intraindustry trade between Western European countries. They also show that the
difference in service-link costs and location advantages are empirically relevant
and play a significant role in determining the magnitude of trade in machinery
parts and components, as stated by the fragmentation literature.10
Jones et al. (2005), who analyze the areas of NAFTA, EU-15 and East Asia,
conclude that the optimal degree of fragmentation depends on the size of the
market, as the scale of production would determine the length to which such a
division of labor can proceed. The importance of the size of the market on trade
and fragmentation can be also found in the research by Egger and Falkinger
(2002 and 2003b) and Burda and Dluhosch (2002).
The conclusion drawn from the brief review of the literature on fragmentation is
that not only factor endowment differences, but also service-link costs are the
main driving forces behind the fragmentation of the production process and
consequently of trade in parts and components. These service-link costs include
10
Other studies that highlight the importance of service-link and location advantages include
Bergstrand and Egger (2006) and Golub et al. (2007).
11
aspects such as political settings, institutional and infrastructure quality. Hence,
here we consider these factors as the key determinants of parts and components
trade.
5. Empirical analysis
MODEL SPECIFICATION AND ESTIMATION METHODOLOGY
Following previous empirical research, we analyze the nature of trade in parts
and components in the Western Balkans by estimating a gravity model. 11 This
model, initially developed by Tinbergen (1962) and later expanded by Anderson
(1979), explains the volume of bilateral trade flows according to the size of the
trading economies and bilateral trade costs (variables such as physical distance,
common border or language are considered).
Despite lacking strong theoretical foundation, gravity models have shown
significant empirical robustness and explanatory power for describing trade flows.
Recently, Bergstrand and Egger (2010) developed a theoretical model that
encompasses bilateral final goods trade, intermediate goods trade and foreign
direct investment flows. This model simultaneously estimates gravity equations
for all these flows.
The gravity equation employed in this research augments the standard gravitytype variables i.e. economic size (size), distance (dist), and common border
(border) with other factors that have been suggested by the fragmentation
literature, such as differences in factor endowments (endow) and market size
dissimilarities (ssize). We also include variables that take into account the quality
of infrastructure, institutional similarity or political-economic agreements (Xk).
More specifically, the estimating equation takes the following form:
11
Gravity models have been widely used in the empirical literature of trade in parts and
components. See, for instance, the papers by Athukorala and Yamashita (2006) and Kimura et al.
(2007).
12
ln( pctrade ) ijt = β 0 + β 1 size ijt + β 2 dist ij + β 3 border ij + β 4 endow ijt + β 5 ssize it +
+ ∑ γ k X k ,ijt + λt + μ ij + ε ijt
k
where i and j are home and host-country indexes, respectively and t denotes
time. The error term comprises (fixed or random) unobserved bilateral effects, μij,
and the remaining error εijt, assumed to be independent across countries and
over time. The countries included in the data set are presented in Appendix
(Table A1). The years analyzed are 2000, 2003, 2006 and 2009.12 As mentioned,
the dependent variable stands for the trade flows in parts and components
between the WB country and its trading partner. The definitions and sources of
all variables are detailed in Table A2 from the Appendix .
The above equation has been estimated using a panel data approach. This
methodology allows us to control for country-specific differences in technology,
production and socioeconomic factors, thus avoiding the misspecification
problems that individual heterogeneity involves.13 Moreover, it is a well known
fact that panel data provide more degrees of freedom, less collinearity and
therefore more efficiency. The decision regarding whether to consider
unobserved country-specific effects as fixed or random was made on the basis of
the Hausman test. The models have been estimated with both home-country and
country-pair effects.14 For the sake of robustness, we have also estimated the
model using Ordinary Least Squares (OLS). The results of these last estimations
are available upon request.
DATA AND VARIABLES
Data for parts and components trade (pctrade) were drawn from the United
Nations Commodity Trade Statistics Database (UN Comtrade database) using
the Standard International Trade Classification (SITC) Revision 3. Machinery and
transport equipment (group 7) and miscellaneous manufactured articles (group 8)
12
Data for 2004 were used for Serbia and Montenegro because data for 2003 were not available.
See Hsiao (1986).
14
The Hausman test has been obtained from the models with country-pair effects.
13
13
provide the basis for the empirical analysis. It contains a total of 145 product
categories.
Trade in parts and components includes imports of country i from country j, as
well as exports from country i to country j, for which data on parts and
components are available. Hence, not only parts and components imports are
considered, but also two-way trade volumes between countries. There are 5
different groups (the WBC) in total out of which each country is analyzed
according to its bilateral trade relations with a set of 20 country pairs.
Following previous applications of the gravity model, we use home and foreign
country GDP to measure market size, (Egger and Egger, 2005). The importance
of this variable for the international fragmentation of production has been
emphasized on many occasions. According to Jones et al (2005), the optimal
degree of fragmentation depends on the size of the market, as long as the scale
of production determines the length to which such a division of labor can
proceed. This idea would be in line with the new theory of trade under imperfect
competition. For Grossman and Helpman (2005), in a ‘thicker market’ that
includes a greater number of firms, it should be easier to find a partner firm with
the appropriate skills and technology to produce the fragmented component. So,
the larger the international market, the greater the opportunities to produce
differentiated intermediate goods.
The new trade theory and new economic geography models have further pointed
out the importance of differences in market size in determining the pattern of
trade (Helpman, 1987). According to these models, the more similar countries
are in size, the larger the share of IIT. Thus, trade in parts and components
should be positively affected by the fact that trading partners are more similar in
14
size. The similarity of market size is captured here by the similarity index
proposed by Helpman (1987).15
As noted previously, the exploitation of comparative advantages that stems from
differences in relative factor endowments is viewed by many authors as one of
the main reasons for international fragmentation (Arndt 1997; Deardorff 2001a;
Jones and Kierzkowski 1990 and 2001b). According to these authors,
international fragmentation is more likely to occur between countries with
different factor endowments, based on the standard comparative advantage
justification for trade. As in other applications of the gravity model, we proxy the
differences in factor endowments by the difference in per capita GDP between
the WBC and their trading partners.
Transportation costs (measured by geographical distance) between production
stages are commonly used as service-link costs (Kimura et al., 2007). Bergstrand
and Egger (2006) suggest that the level of trade costs should negatively impact
the share of intra-industry trade. According to Athukorala and Yamashita (2006)
and Golub et al. (2007), transportation costs might be more relevant for trade in
parts and components than for trade in final goods. They argue that
transportation costs would rise due to the number of shipments among different
production stages before final assembly takes place. We also include a common
border dummy and two regional variables (saa and yugo) that take into account
whether or not the WB country has signed a Stabilization and Association
Agreement (SAA) with the EU and whether or not the trading partners are
republics of the former Yugoslavia, respectively.
More recently, many studies have also insisted on the importance of the quality
of infrastructure and institutional differences in the international fragmentation of
15
The similarity of country size index à la Helpman (1987) is defined as:
⎡ ⎛
⎞
⎞ ⎛
GDPit
GDPjt
⎟⎟
⎟⎟ − ⎜⎜
log ⎢1 − ⎜⎜
⎢⎣ ⎝ GDPit + GDPjt ⎠ ⎝ GDPit + GDPjt ⎠
2
2
⎤
⎥
⎥⎦
,
where indices i and j refer to home and foreign countries, respectively, t denotes time and GDP is
a country’s real GDP.
15
production.16 Infrastructure (infra) is viewed as a cost-effective means of lowering
trade costs and thereby promoting the internationalization of firms. For Francois
and Manchin (2007), propensity to take part in a trading system depends on
access to well-developed infrastructure. Insofar as higher quality infrastructure
reduces communication and coordination costs, a positive impact of this variable
on trade in parts and components is expected. As shown by Cheptea (2007), an
improvement at the institutional level promotes trade integration. According to
this author, homogeneity in the quality of institutions (instit) may also enhance
trade in parts and components. Similar norms of behavior and levels of trust in
doing business may make trading between countries easier (Beugelsdijk and van
Schaik, 2001). Institutional similarity means that firms will be more familiar with
the formal procedures and informal practices in the other country.
In our model, we have also included the relative exchange rate of the country
(exch).
Previous empirical work (Swenson, 2000) shows a significant and
negative impact of dollar depreciation on outward processing in the case of US
firms in terms of foreign inputs becoming more expensive. In this line, currency
depreciation in the WBC might have a positive impact on parts and components
exports to their trading partners. Finally, we have added foreign direct investment
in the home country (fdi) as an explanatory variable. As the affiliates of the MNC
are a direct result of capital flows in the form of FDI in the host country, we would
expect this variable to have a positive impact on trade in parts and components.
Affiliates usually perform final assembly or processing stages using imported
intermediate goods from the parent firm. According to Feenstra and Hanson
(1997), the growth of capital stock in the host country encourages the flow of
intermediate goods for further processing between the two countries.
ESTIMATION RESULTS
Table 3 presents the estimate coefficients for parts and components trade with
home-country specific effects. For comparative purposes, we also present these
16
See, for instance, the work by Egger and Egger (2005) and Jones et al. (2005).
16
estimations for final goods trade in Table 4. 17 These models have also been
estimated with country-pair effects and results are shown in Tables A3 and A4 in
Appendix, respectively.
In these tables, two different models are estimated for each trade flow: a baseline
model that includes the standard gravity variables together with the factor
endowment variable and similarity in size (Model 1) and an extended model,
which adds other country-specific variables (Model 2). Both imports and exports,
as well as total trade (imports plus exports), have been calculated.
(Insert Tables 3 and 4 here)
As can be seen, the outcomes generally support the hypothesis drawn from the
fragmentation literature regarding the importance and signs of the explanatory
variables. While greater distance discourages bilateral parts and components
trade in the WBC, market size significantly promotes it. This last circumstance is
in line with the hypothesis that fragmentation of production becomes more costefficient the larger the market (Jones and Kierzkowski 1990). Similar findings are
presented in Jones et al. (2005) and Kimura et al. (2007). Furthermore, the
results are generally the same for all regressions in both models with homecountry and country-pair effects, suggesting that the results are robust across
specifications.
As expected, the distance variable is negative and strongly significant, verifying
the hypothesis that distance-related service-link costs may deter trade in parts
and components. According to Jones and Kierzkowski (2001), international
fragmentation is more favorable when service-link costs are lowered.
Furthermore, if we look at exports and total trade this coefficient is clearly higher
for parts and components than for final goods trade. This would imply that the
influence of distance-related costs on the IPN is greater due to the nature of the
production process and multiple border crossings.
17
The outcomes of estimating total trade in SITC Rev. 3 groups 7 and 8 are available upon
request.
17
The variable that represents similarity in country size also displays the expected
positive and significant coefficient in parts and components imports and total
trade. However, we find a negative relationship between country-size similarity
and exports of parts and components. One possible explanation for this
surprising result could be that WBC trade shifted towards the EU countries during
the considered period (as presented in Section 2). These countries are quite
different in relative country size to the WBC.
In line with the predictions made by models on vertical IIT, significant differences
in GDP per capita have a positive influence on both imports and exports. As
mentioned previously, in these models the volume of vertical trade or
fragmentation tends to increase the greater the differences in factor endowments
and factor prices between two countries. Hence, our estimations would support
the hypothesis that efficiency seeking is an important determinant in the parts
and components trade of the WBC. This variable is significant for exports in parts
and components, explaining the marked increase in exports from the WBC
presented in Section 2. Similar findings are observed in Egger and Egger (2005).
Our results also show that the greater the degree of similarity in institutions
(economic freedom and legal certainty) in trading partner countries, the more
trade flows in parts and components. This is consistent with the idea that
institution quality is relevant for both establishing affiliates for processing parts
and components in partner countries and for companies becoming trading
partners when dealing with arm’s-length transactions. Moreover, the coefficients
for this variable are more relevant for parts and components than for final goods
trade. This reflects that regulatory issues and institutional similarity are more
important when firms need to engage in production partnerships, compared to
single trade relations in final goods.
As mentioned above, another determinant related to service-link costs is the
quality of infrastructure. This variable records a clearly positive and significant
influence on bilateral trade in parts and components. This coincides with the
18
results obtained by Jones et al. (2005) and Egger and Egger (2005). Both studies
conclude that infrastructure quality as part of service-link costs is extremely
relevant in promoting parts and components trade. Furthermore, in view of the
fact that there are more shipments between production segments within the IPN,
infrastructure quality markedly favors parts and components trade when
compared to final goods trade.
Although the shared border dummy has the expected positive sign, it becomes
insignificant in the extended model once we control for other variables, such as
infrastructure, institutions and regional trade. This is not surprising if we consider
that the WBC do not share a border with their most important trading partners
(the EU-15), as presented in Section 2. We also find the yugo dummy variable
highly significant in all regressions. The coefficient of this variable is considerably
higher in trade in parts and components than in the other two types of trade,
suggesting the presence of intra-regional ties and the potential of intra-regional
production networks, reflected by the trade in parts and components. However,
the dummy variable for SAA is not significant in either imports or exports. This
could be due to the fact that the only two countries that had signed SAA before
2007/2008 were Croatia and Macedonia, so the overall impact on the region is
small.
The coefficient for the bilateral exchange rate, albeit insignificant, appears to
have a positive impact on exports of parts and components and total trade, which
confirm the idea that a devaluation of the currency will foster exports of parts and
components. One possible explanation for this variable not being significant
would be that most of the sample countries have a de facto peg to the euro.
Interestingly, the results for the FDI variable are rather mixed. We should
interpret this outcome with a certain degree of caution since there were no
disaggregated data for FDI by country of origin for the WBC to match the FDI
flows with the respective bilateral trade in parts and components. Moreover,
19
excluding this variable from the model does not affect the significance of the
other variables (results are available upon request).
From the above empirical outcomes, we can derive the following conclusions.
First, our findings support the idea that the fragmentation process in the WBC is
not only efficiency-seeking but also market-seeking. Firms that seek to lower
their production costs through fragmentation should look to larger markets in the
region, as market size determines the cost-efficiency of the service-link costs this
process entails. But the importance of market size may also indicate that marketseeking decisions for locating some firms are also playing an important role.
Second, geographical and institutional distance will discourage trade in parts and
components. According to our results, policies designed to implement incentives
for foreign investors are not sufficient to participate in the IPN. Improving the
institutions to alleviate cost should be considered a priority strategy for
policymakers. Third, governments should also recognize that developing quality
infrastructure in the region is of vital importance to join the international division
of labor and trade, as a higher quality of infrastructures promotes trade
integration. Finally, they should be more aware of the high trade potential to be
exploited from the intra-regional ties between the republics of the former
Yugoslavia, especially in developing regional production networks.
6. Conclusions
A specific form of international production emerges when some stages of the
production process are located in several countries attending to different country
characteristics. International fragmentation and international production networks
are thus created. The result of this process is increased cross-border trade in
parts and components.
Throughout the last decade, the WBC have witnessed a substantial increase in
trade in parts and components. This suggests that the WBC, as part of their
economic modernization process, have played an active role in production-
20
sharing networks, especially within the Europe. Thus, identifying the nature and
determinants of this type of trade is of particular interest.
According to the fragmentation literature, factor endowment differences and
service-link costs are the driving forces behind the fragmentation of the
production process. This theory is confirmed by our estimates, which show how
factor endowment differences and market size significantly increase the
fragmentation of production in this region, while distance deters it. As expected,
these variables have a greater impact on trade in parts and components than on
final goods trade.
Infrastructure quality also seems to be of great importance when establishing
international production networks. Significant payoffs could be obtained from
improving the infrastructure in the WBC, as reliable and inexpensive
infrastructure facilitates the fragmentation process.
The degree of similarity in economic freedom and legal certainty in trading
partner countries represents another key factor for parts and components trade
in the region. Once again, the influence is much greater on parts and
components trade than on final goods trade. This result supports the fact that
institutional framework is more relevant when locating part of the production
process abroad or performing arm’s-length transactions.
Finally, our estimates confirm that, as predicted by the theory on international
fragmentation, a reduction in the cost of trade associated with regional
integration processes has favoured the international division of production
processes. We find that the regional ties between the republics of the former
Yugoslavia are still very active, even after a decade of wars and conflicts. The
importance of these effects is seemingly higher for parts and components trade
than for final goods trade.
The results of this study are in line with the established fragmentation literature
and provide support for the main arguments therein. We are aware that the
21
determinants of the international fragmentation of production might differ from
industry to industry depending on countries’ patterns of specialization. Thus, a
future avenue of research to draw more detailed policy implications could be to
perform an in-depth industry-by-industry analysis.
22
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25
Appendix
We considered the Standard International Trade Classification (SITC) Revision 3
as the most appropriate in terms of detail, time, length and comprehensiveness.
The groups used in our data are machinery and transport equipment (group 7)
and miscellaneous manufactured articles (group 8). The goods classified as parts
and components are listed below and the rest of the goods in groups 7 and 8 are
classified as final goods.
Code list:
7119,7128,7131,7132,7133,7138,7139,71441,71449,7149,7169,71819,71878,71899,72
119,72129,72139,72198,72199,7239,72439,72449,72467,72468,72488,7249,7259,7268
9,7269,72719,72729,72819,72839,72847,7285,7351,7359,73719,73729,73739,73749,7
4128,74135,74139,74149,74159,74172,7419,7429,7438,7439,74419,7449,,74519,7452
9,74539,74568,7459,7469,7479,74839,7489,7491,7591,7599,7649,77129,7722,7723,77
24,7725,7726,7728,77429,77549,77579,77589,7761,7762,7763,7764,77688,77689,778
17,77819,77829,77833,77835,77848,77869,77879,77883,77885,7889,7841,7842,7843,
78535,78536,78537,78689,7919,7929,81211,81215,81219,8138,8139,82119,8218,8711
9,87139,87149,87199,87319,87329,87412,87414,87424,8742,87426,87439,87449,8745
87456,87469,87479,8749,88114,88115,88123,88124,88134,8136,8859,89111,89113,89
12,8919,8941,8989,89935,89937,89949
26
Table A1. Regions and countries included in the dataset
Region
Country
Western
Balkans
Albania, Bosnia and Herzegovina, Croatia, Macedonia, Montenegro and
Serbia
EU-15
Austria, Belgium, France, Germany, Greece, Italy, Luxemburg, Netherlands,
Sweden, United Kingdom
EU-1018
Bulgaria, Czech Republic, Hungary, Slovenia
EFTA
Switzerland
East Asia
China, Japan
Others
Turkey
18
The EU-10 countries are: Bulgaria, the Czech Republic, Hungary, Slovenia, Slovakia, Romania,
Latvia, Lithuania, Estonia and Poland
27
The table below presents the definition of each of the variables used and the
data sources.
Table A2. Definitions and data sources
Abbreviation
Definition
Data Source
pcimports
Logarithm of P&C Imports in the WBC
UN Comtrade database
pcexports
Logarithm of P&C Exports from the WBC
UN Comtrade database
pctotal
Logarithm of P&C total trade in the WBC
UN Comtrade database
size
Logarithm of the GDP of the home country multiplied by the
GDP of the foreign country
World Development
Indicators - World Bank
dist
Weighted geographical distance between countries
Institute for Research on the
International EconomyCEPII distance database
border
Dummy variable (1 if the partner countries shares a border
and 0 if not)
endow
An index of per capita GDP of i relative to that of j, adjusted
by the bilateral exchange rate
World Development
Indicators - World Bank
ssize
Logarithm of similarity index by Helpman 1987
World Development
Indicators - World Bank
infra
Logarithm of the minimum value of the number of telephone
lines in both countries
World Development
Indicators - World Bank
instit
Absolute difference in the Freedom House index between
partner countries
Freedom House - Freedom
in the World Index
yugo
Dummy variable (1 if a WB country was part of the former
Yugoslavia and 0 if not)
saa
Dummy variable (1 if a WB country has an SAA with the EU
and 0 if not)
fdi
Logarithm of the stock of foreign direct investment in the
WB country
World Development
Indicators - World Bank
exch
Real effective exchange rate between countries
UNCTAD database
28
Table A3. Estimation results for parts and components trade. Country-pair fixed effects
Parts and components
Dependent
variable
Imports
Model 1
Model 2
Random
Effects
0.720 ***
(0.056)
-0.341
(0.241)
1.231 **
(0.542)
-0.238
(0.184)
0.101
(0.127)
size
dist
border
endow
ssize
-17.96 ***
(2.832)
-0.067
(0.119)
-0.240 *
(0.143)
-0.662 **
(0.307)
-27.93 ***
(7.339)
-21.78 ***
(5.760)
374
0.5022
352
0.5008
351
0.3629
329
0.7195
378
0.5391
355
0.7395
4.72
0.1936
16.23
0.0392
20.10
0.0002
11.70
0.1653
8.57
0.0357
13.38
0.0995
instit
yugo
saa
fdi
exch
Num. of
observations
Adjusted R
Hausman
Test
2
Fixed
Effects.
0.887 ***
(0.135)
Fixed
Effects
0.752 ***
(0.105)
-0.061
(0.302)
0.319
(0.348)
0.635 *
(0.388)
0.088
(0.101)
Omitted
-0.452
(0.358)
0.482
(0.320)
Imports+Exports
Model 1
Model 2
Random
Effects
0.921 ***
(0.105)
-3.072 ***
(0.356)
0.002
(0.435)
0.633 ***
(0.204)
-0.284 *
(0.164)
1.827 ***
(0.331)
0.359 ***
(0.119)
1.639 ***
(0.409)
0.064
(0.198)
-0.013
(0.149)
0.076
(0.067)
-18.83 ***
(3.581)
infra
const
Exports
Model 1
Model 2
Fixed
Effects
0.678 ***
(0.057)
-16.92 ***
(3.249)
Random
Effects
0.896 ***
(0.061)
-0.836 ***
(0.177)
0.811 ***
(0.299)
0.072
(0.078)
0.106
(0.103)
0.601 ***
(0.187)
0.252 ***
(0.083)
1.908 ***
(0.317)
-0.008
(0.103)
-0.172 **
(0.082)
0.006
(0.048)
-24.85 ***
(2.673)
-0.087
(0.200)
0.307
(0.206)
29
Table A4. Estimation results for final goods trade. Country-pair fixed effects
Final goods
Dependent
variable
size
dist
border
endow
ssize
Imports
Model 1
Model 2
Random
Effects
0.801 ***
(0.064)
-0.703 ***
(0.236)
0.877 **
(0.424)
0.048
(0.184)
-0.072
(0.122)
infra
instit
yugo
Fixed
Effects
1.027 ***
(0.227)
-0.338
(0.336)
0.001
(0.230)
0.897 ***
(0.270)
0.119
(0.088)
Omitted
-0.442
(0.363)
0.135
(0.462)
-0.654 **
(0.278)
1.028
(0.677)
1.307 ***
(0.426)
0.284 **
(0.122)
Omitted
379
0.5952
6.19
0.1026
exch
Num. of
observations
2
Adjusted R
Hausman
Test
Fixed
Effects
0.823 ***
(0.117)
-18.18 ***
(2.783)
fdi
const
Fixed
Effects
0.875 ***
(0.130)
-0.110
(0.113)
-0.213 *
(0.124)
-0.392
(0.368)
-27.55 ***
(6.669)
saa
Exports
Model 1
Model 2
Imports+Exports
Model 1
Model 2
Random
Effects
0.767 ***
(0.060)
-0.885 ***
(0.231)
1.012 ***
(0.375)
0.194
(0.146)
-0.121
(0.123)
Fixed
Effects
0.803 ***
(0.107)
-0.361
(0.340)
0.020
(0.214)
0.728 ***
(0.202)
0.135 **
(0.061)
Omitted
-24.72 ***
(6.889)
0.121
(0.198)
-0.292
(0.234)
0.802 *
(0.429)
-37.37 ***
(11.130)
-15.07 ***
(2.438)
-0.082
(0.091)
-0.129
(0.107)
-0.483 **
(0.246)
-23.16 ***
(5.464)
356
0.5796
366
0.4045
343
0.4576
379
0.5928
356
0.6382
18.95
0.0151
10.71
0.0134
18.47
0.0180
4.37
0.2243
21.50
0.0059
30
FIGURES
Figure 1. Annual growth in parts and components trade. Period 2000-2010
40,0%
30,0%
20,0%
10,0%
World trade
WBC trade
0,0%
2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010
-10,0%
-20,0%
-30,0%
Source: UN Comtrade and author’s own calculation.
31
TABLES
Table 1. Foreign direct investment as % of GDP
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
3.9
5.1
3.0
3.1
4.6
3.1
3.6
6.2
7.4
8.0
9.4
2.7
5.2
6.0
2.1
6.9
13.0
4.0
4.1
2.8
4.6
6.0
2.5
7.1
2.6
5.9
5.6
4.0
1.6
6.3
6.9
6.5
13.6
8.4
8.6
5.3
8.6
6.0
1.4
4.5
2.1
1.4
0.5
3.2
0.9
1.6
3.8
7.2
Source: World Development Indicators.
4.3
8.1
17.0
17.1
13.8
20.8
11.0
Albania
Bosnia and
Herzegovina
Croatia
Macedonia
Serbia and
Montenegro
Table 2: Trade in (total) machinery and transport equipment and parts and components of the
same groups: 2000-2009 (mil. US$)
Machinery final goods
trade
Imports
Exports
World
2000
2004
2009
Western
Balkans
2000
2004
2009 *
2009 **
EU-10
2000
2004
2009
EU-15
2000
2004
2009
Imports
P&C
trade
Exports
P&C/Machinery final
goods
Imports
Exports
2,203,795
3,075,915
3,793,472
72%
2,162,897
3,031,530
3,848,402
77%
1,117,222
1,474,657
1,706,771
52%
1,117,097
1,456,353
1,634,764
46 %
51%
48%
45%
52%
48%
42%
4,823
13,614
16,721
14,104
192%
2,291
5,455
7,925
6,487
183%
678
2,171
2,847
2,425
257%
437
1,119
2,449
1,940
343%
14%
16%
17%
17%
19%
21%
31%
30%
52,382
109,529
152,759
191 %
52,046
115,869
211,585
306%
28,451
57,974
91,989
223%
22,907
54,895
80,651
252%
54%
53%
60%
44%
47%
38%
780,221
835,583
346,150
346.907
44%
1,140,510
1,220,609
454,234
487.889
40%
1,289,273
1,335,803
456,219
507.219
35%
65%
59%
31%
46%
* Data for the WBC with Bosnia and Herzegovina. The comparison is with 2004.
** Data for the WBC without Bosnia and Herzegovina. The comparison is with 2000.
Source: UN Comtrade database and own calculations.
42%
40%
38%
32
Table 3. Estimation results for parts and components trade. Home-country fixed effects
Parts and components
Dependent
variable
size
dist
border
endow
ssize
infra
instit
yugo
saa
fdi
exch
const
Num. of
observations
Adjusted R
2
Imports
Model 1
Model 2
Random
Fixed
Effects
Effects
0.743 ***
1.158 ***
(0.102)
(0.051)
-0.488 **
-0.689 **
(0.181)
(0.231)
1.148 ***
0.950
(0.267)
(0.522)
-0.225 *
0.176
(0.100)
(0.110)
0.051
0.382 **
(0.152)
(0.116)
1.674 **
(0.611)
0.430 ***
(0.069)
2.073 ***
(0.259)
0.132
(0.067)
-0.706 ***
(0.169)
0.003
(0.080)
-18.17 **
-40.60***
(4.577)
(3.118)
Exports
Model 1
Model 2
Fixed
Random
Effects
Effects
0.872 ***
0.868 ***
(0.115)
(0.090)
-2.921 ***
-3.067 ***
(0.481)
(0.383)
0.182
0.008
(0.794)
(0.983)
0.349 **
0.681 ***
(0.091)
(0.070)
-0.313 **
-0.354 ***
(0.126)
(0.102)
1.938 ***
(0.308)
0.450 ***
(0.155)
1.452 ***
(0.275)
-0.134
(0.175)
0.224 ***
(0.081)
0.082 *
(0.046)
-10.62 **
-17.58 ***
(3.954)
(1.451)
Imports+Exports
Model 1
Model 2
Fixed
Random
Effects
Effects
0.881 ***
0.855 ***
(0.106)
(0.064)
-0.914 ***
-0.916 ***
(0.228)
(0.178)
1.024 ***
0.872 *
(0.220)
(0.481)
0.131
0.077 *
(0.089)
(0.043)
0.152
0.043
(0.111)
(0.057)
0.664 ***
(0.141)
0.386 ***
(0.083)
1.851 ***
(0.199)
-0.010
(0.075)
-0.106
(0.092)
0.013
(0.029)
-21.53 ***
-23.10 ***
(4.835)
(2.041)
374
352
351
329
378
355
0.4308
0.6543
0.4935
0.7230
0.5628
0.7438
Data source: Authors’ own calculation based on UN Comtrade database.
Notes: figures in parenthesis are the standard errors. ***; ** and * indicate that the results are
statistically significant at the 1; 5 and 10 percent levels, respectively
33
Table 4. Estimation results for final goods trade. Home-country fixed effects
Final goods
Dependent
variable
size
dist
border
endow
ssize
infra
instit
yugo
saa
fdi
exch
const
Num. of
observations
Adjusted R
2
Imports
Model 1
Model 2
Random
Fixed
Effects
Effects
0.879 ***
1.200 ***
(0.085)
(0.125)
-0.596 ***
-0.731 ***
(0.136)
(0.134)
0.890 ***
0.784 *
(0.352)
(0.339)
0.020
0.332 **
(0.082)
(0.106)
0.103 **
0.376 **
(0.043)
(0.106)
1.193 **
(0.384)
0.281 ***
(0.061)
1.714 ***
(0.299)
0.080
(0.148)
-0.710 ***
(0.116)
-0.021
(0.062)
-22.24 ***
-38.71 ***
(3.545)
(4.758)
Exports
Model 1
Model 2
Fixed
Fixed
Effects
Effects
0.880 ***
0.777 **
(0.136)
(0.202)
-3.063 ***
-2.643 ***
(0.201)
(0.307)
0.454
0.700
(0.581)
(0.625)
0.204 **
0.203
(0.058)
(0.176)
0.489 ***
-0.483 **
(0.046)
(0.140)
0.356
(0.631)
0.182
(0.115)
1.558 *
(0.644)
0.291 ***
(0.036)
0.179 *
(0.071)
0.206 *
(0.092)
-8.86
-9.35
(5.548)
(8.379)
Imports+Exports
Model 1
Model 2
Random
Fixed
Effects
Effects
0.794 ***
0.744 ***
(0.057)
(0.069)
-0.845 ***
-0.751 ***
(0.080)
(0.057)
0.982 **
0.978 ***
(0.304)
(0.294)
0.154 *
0.240 ***
(0.060)
(0.059)
-0.061
-0.140 ***
(0.088)
(0.042)
0.746 ***
(0.115)
0.205 ***
(0.048)
1.449 ***
(0.301)
0.187 ***
(0.060)
-0.143 **
(0.073)
0.047 *
(0.027)
-16.51 ***
-17.45 ***
(2.730)
(2.263)
379
356
366
343
379
356
0.6024
0.7210
0.5979
0.6856
0.5626
0.7777
Data source: Authors’ own calculation based on UN Comtrade database.
Notes: figures in parenthesis are the standard errors. ***; ** and * indicate that the results are
statistically significant at the 1; 5 and 10 percent levels, respectively
34