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Vienna University of Economics & B.A.
Department of Economics Working Paper Series
Abstract ― The paper investigates the formation of wages in the New Member States in
Central and Eastern Europe, in particular the question what the relative role of national
and sectoral factors is. While the labor relations in these countries are still in the process
of change, some pattern and national differences have emerged. The question is thus to
what extent these differences in labor relations are reflected in wage formation. The
literature on Western OECD economies is unanimous that coordination of wage
bargaining does reduce the wage spread, but disagrees on its effects on unemployment
and inflation. The paper analyses wage formation in Slovenia, Slovakia, Hungary,
Poland, the Czech Republic and Lithuania by means of a panel analysis for
manufacturing sectors. The average wage (in the total economy) serves as a national
factor and sectoral productivity serves as a sectoral factor. In variations of the basic
estimation equation the role of FDI and openness and of capital intensity and skill are
also discussed. The results between countries are compared with the recent index of the
coordination of collective bargaining by Visser (2005) and with cross country data on
union density.
Keywords: wage formation, CEEC, wage spread, labor relations, FDI
JEL-Classification: P23, J50, J30
1 The paper received financial support from the FESTO fellowship of the Vienna University of Economics and
Business Administration. The authors are grateful to Paul Ramskogler for excellent research assistance and to
Markus Leibrecht, Thomas Grandner, Aleksandra Riedl and the participants at the wiiw Seminar in International
Economics for helpful comments. The usual disclaimers apply.
2 corresponding author: Engelbert.stockhammer@wu-wien.ac.at; Dept. of Economics, VWL 1,
Wirtschaftsuniversität Wien, Augasse 2-6, 1090 Wien, Austria
3 oonaran@itu.edu.tr ; ozlem.onaran@wu-wien.ac.at; Istanbul Technical University, Turkey, &
Wirtschaftsuniversität Wien, Austria, Istanbul Technical University, Macka, Istanbul
National and sectoral factors in wage formation in
Central and Eastern Europe 1
Engelbert Stockhammer 2 and Özlem Onaran 3
Working Paper No. 100, Dec 2006
2
National and sectoral factors in wage formation in Central and Eastern Europe
Actual labor markets rarely function like the spot markets that dominate introductory
microeconomic textbooks. In most developed countries wages are bargained between labor
unions and employers or employer organizations. Countries however differ substantially with
respect to the degree of centralization at which collective bargaining takes place. Bargaining
can take place at the firm level, like in many Anglo-Saxon countries, or in a coordinated
fashion at the sectoral or national level (like in Skandinavian countries), with various
intermediate forms existing. In the Central and Eastern European Countries (CEEC) labor
relations have only been recently established in the course of transition. Since the breakdown
of Communism labor relations have been shaped by large scale privatization, large FDI
inflows and labor policies guided by the countries’ desire to join the EU (Aguilera and Dabu
2005). This implied the setting up of modern labor laws, including the right of workers to
form labor unions and to bargain collectively (Schroeder 2004).
While most CEECs are characterized by firm-level bargaining structures similar to the Anglo-
Saxon model, remarkable differences between countries have emerged so far that reveal a
surprising variety of labor relations in CEECs. Slovenia has highly organized labor relations
that resemble Skandinavian or Austrian patterns with collective bargaining rates close to
100%, whereas in Lithuania only 10% of employees are covered by collective bargaining
agreements. This can be called disorganized labor relations. The other countries are
intermediate cases with weakly organized labor relations.
The question arises, what the effects of different bargaining regimes on economic outcomes
are. For Western economies there is a rich literature on this topic (EC 2003, OECD 2004)
with hypotheses ranging from the liberal hypothesis that performance with respect to
3
unemployment and inflation increases (linearly) with the degree of disorganization (market-
orientedness) of labor relations on the one hand, and the coroporatist hypothesis that the
degree of organization has a positive effect on the other hand (Traxler et al 2001). As an
intermediate position the hump-shaped hypothesis (Calmfors and Driffill 1988) argues that
intermediate bargaining structures will deliver worse outcomes than consistently organized or
disorganized labor relations. What these hypotheses share is the assertion that the degree of
organization has a negative effect on the wage spread, which has received wide empirical
support for Western countries (OECD 2004). It is this latter issue that is the subject of this
paper.
The paper investigates the formation of manufacturing wages in the NMS in CEE, in
particular the relative role of national and sectoral factors. Average wages (of the total
economy) and sectoral productivity serve as the respective proxies. Wage formation is
analyzed for Slovenia, Slovakia, Hungary, Poland, the Czech Republic and Lithuania by
means of a panel analysis for manufacturing sectors. In addition trade openness and the size
of FDI stocks will serve as control variables. Further wage formation will be allowed to differ
across sectors according to capital intensity and skill groupings. The results between countries
are compared with the recent classification of labor relations by Visser (2005) and Kohl and
Platzer (2004).
The literature (available in English) on CEECs during and after transition has had strong
focus on growth. Only recently have issues of wage formation gained more interest, often
linked to the issue of relocation and its effects. Here two lines of research have emerged. First,
the analysis of relocation to Eastern economies has highlighted the issue of wage disparities
according to skills. Egger and Stehrer (2003) find that intermediate exports and imports have
a positive effect on the unskilled wage share in the Czech Republic, Hungary and Poland
4
based on dynamic panel estimations on the 2-digit level. Second is the issue of regional wage
disparities. Egger, Huber and Pfaffermayr (2005) conclude that trade liberalization has
fostered regional divergence rather than convergence. Iara and Traistaru (2004) find that
regional wages are responsive to regional unemployment in Hungary, Poland and Bulgaria,
but not in Romania. The study is based on a panel analysis with regional (NUTS 3) (monthly)
wage and (annual) unemployment data.
The paper is structured as follows. Section 2 provides the theoretical background. Section 3
discusses labor relations in the CEECs and differences between countries. The data and some
stylized facts are presented in section 4. Section 5 presents the regression results. Particular
attention will be paid to issues of robustness and to sectoral characteristics in terms of
outward orientation and skill content. Finally section 6 concludes.
Theoretical background
A frequently found assertion, based on data of Western OECD countries, is that highly
organized labor relations will give rise to wage compression, or, more positively put, lower
inequality among wage earners. The OECD finds a “robust relationship between the
organisation of collective bargaining and labour market outcomes, (…) overall earnings
dispersion tends to fall as union density and bargaining coverage and centralization/co-
ordination increase” (OECD 2004, 166). This will be called the linear wage compression
hypothesis, that is the hypothesis that more organized labor relations lead in a linear way to
wage compression and thus to a dominance of national factors in wage setting.
While there has been little disagreement over the effect of bargaining organization on wage
dispersion, there has been a broad and controversial debate on the macroeconomic effects of
5
wage bargaining systems. This warrants a brief digression. Wage compression has been held
responsible, among other factors, for the rise in unemployment in Europe (Siebert 1997, Blau
and Kahn 2002), though the evidence is inconclusive (Howell and Huebler 2005). In
summarizing the literature on labor relations and macroeconomic performance Traxler et al
(2001) distinguish between a neoliberal, neoclassical, corporatist and hump-shaped
hypotheses. These refer to the outcome in terms of unemployment (or inflation). The
neoliberal argument holds that economic performance will deteriorate with the degree of
organization of bargaining. The neoclassical argument holds that bargaining (at least in the
long run) does not matter, while the corporatist argument claims that organized bargaining
systems are superior to disorganized ones. There is also a stream that has held the degree of
organization of labor relations will have U-shaped effects on macroeconomic outcomes. This
view gained prominence through the seminal paper by Calmfors and Driffill (1988), who
argued that highly centralized as well as highly decentralized bargaining systems may lead to
desirable outcomes (referring to unemployment). Remarkably their paper provided little
evidence for the supposed channel, which is wage moderation.
After two decades of debates, it is fair to say that the evidence as of now is inconclusive.
While OECD (2004) fails to find much of a correlation between bargaining structures and
macroeconomic performance, Calmfors et al (2001) find evidence that coordinated bargaining
is superior to other forms. The recent issue of the OECD Employment Outlook (OECD 2006)
again asserts that highly organized welfare regimes as well as very market oriented regimes
can generate low unemployment.
These debates deal with the effects of labor relations on employment performance. What will
be investigated in this paper is the relation between the institutional setting of wage
bargaining and the relative strength of sectoral and national factors in wage formation. This is
6
an analytical step prior to analyzing the macroeconomic effects of labor relations. Indeed,
much of the debate summarized above presupposes that organized labor relations give rise to
a dominance of national factors in wage setting. However, can we take for granted that this is
the case in CEECs? The questions to be investigated therefore are: are wages mostly
influenced by sectoral or by national factors? Does the nature of labor relations affect the
relative strength of these factors? In this paper, average wages in the total economy will serve
as the key national variable and sectoral productivity serves as the sectoral factor.
At first sight it may appear that the linear wage compression hypothesis is straightforward:
coordinated labor unions will demand higher wages in parallel, thus there is no reason to
expect a wage drift. However, it is less clear that sectoral wages will diverge in a competitive
setting than is usually realized in the current debate. Indeed, in perfectly competitive labor
markets, wages (for a given skill level) would be uniform across all sectors. Supply side
shocks would be reflected in employment changes rather then in wage changes. Why then is it
widely expected that wage differentials are wider in a decentralized setting? What is
supposedly driving the increasing wage spread in Anglo-Saxon countries is a skill-biased
technological change, which is reinforced by globalization. However this crucial role of
technology shocks is often not made clear in the literature (e.g. OECD 2004).
Leaving aside technological shocks, one would expect competitive markets to deliver results
similar to organized labor markets: a relatively uniform wage rate and consequently a minor
effect of sectoral factors.§ Only in intermediate cases with strong sectoral labor unions, which
are able to gain parts of the rents (at the firm or sectoral level), would one expect a strong
§ There are, however, two differences that may be exploited in future research. First, in a coordinated wage
setting the consumption wages ought to be equalized, whereas in a perfectly competitive setting the product
wages ought to be equalized as well. Second, the dynamics may differ. Coordinated wages should by desigen
create equal wages (with little wage dispersion in reaction to shocks), whereas competitive markets, if
imperfectly competitive, will give rise to temporary wage dispersion (to generate the necessary labor flows
across sectors.).
7
effect of sectoral factors in wage formation. This hypothesis will be called the U-shaped
effects of labor relations. Note that this hypothesis, while inspired by arguments like those of
Calmfors and Diffill (1988), is not the argument advanced by them. Their argument refers to
macroeconomic outcomes, not to wage dispersion. According to our hypothesis, both highly
organized and disorganized will generate the same outcome, that is a relatively uniform wage
rate across sectors – but for different reasons. In the case of highly organized labor relations,
wage setting is coordinated intentionally, whereas in the case of disorganized labor relations
labor mobility will ensure that a uniform national wage prevails.
Labor relations in CEECs
The economies and societies of the CEECs experienced dramatic changes in the late 1980s
and 1990s. The transition from a planned economy with state ownership to capitalist market
economies also necessitated the establishment of new procedures to set wages. This transition
was a painful one for most countries with a deep economic recession in the early 1990s. Most
countries reached the per capita GDP of 1989 only in the mid 1990s. Among the countries
discussed here Poland, with a comparatively low starting point, had the most continuous, if
moderate, growth path, and the Baltic states (including Lithuania) had a particularly painful
recession. They reached the pre-transition GDP only at the late 1990s and had lost substantial
ground compared to the Central European transition economies.
At the beginning of transition, not even the actors for wage negotiations were present. With
the exception of Poland, none of these countries had had independent labor unions, nor were
employers organized in associations. Aquilera and Dabu (2005) identify privatization, foreign
direct investment and EU accession as key forces that have shaped the transformation of labor
relations. Generally, the state took an active role in establishing labor relations as labor
8
policies were guided by the countries’ desire to join the EU. This implied the setting up of
modern labor laws, including the right of workers to form labor unions and to bargain
collectively. While labor unions had had strong membership, if little practical influence, in the
previous era, their membership declined dramatically in the course of transition. The early
transition period also witnessed the foundation of independent labor unions and conflict
between the old and new unions (Schroeder 2004).
Overall, labor relations are still in a process of flux, with the state playing a much greater role
than in Western economies. Labor unions as well as employer organizations are usually weak
and states play a much greater role. As consequence minimum wages play a more important
role in wage setting than in Western countries. In addition, states often encouraged tripartite
meetings, which among other things are involved in setting minimum wages. However, some
differences between countries have emerged. Available data on labor relations, which should
be regarded as the best data available rather than as accurate description, is summarized in
Table 1. Most countries have firm-level wage negotiations, only in Slovenia and Slovakia has
bargaining sectoral or national dimensions. This means that substantial parts of the economy
are not covered by these agreements. With the exception of Slovenia, only a minority of
workers, in most countries around 40%, is now covered by collective bargaining agreements.
Lithuania has the lowest share at 10%. Union density varies substantially being highest in
Slovenia (at 40%) and Slovakia (35%), the other countries ranging between 15 and 25%.
Finally, the table also reports the level of the minimum wage as percentage of average
income, since this has been an important means of state policy to influence wages.
Table 1 about here
Visser (2004) also presents a summary measure for the coordination of wage bargaining that
9
allows to rank the countries. Overall, the following picture emerges: Slovenia is a clear
outlier, sometimes called “the Sweden of the East” with highly organized labor relations
similar to Austria or the Scandinavian countries, Slovakia ranks second, still having sectoral
elements in bargaining. Hungary, Poland and the Czech Republic represent intermediate cases
with labor relations that are comparable to the British ones. The ranking between these three
countries is not clear cut. According to Visser the Czech Republic forms the lower end in
terms of degree of organization of labor relations. Clearly Lithuania has the most market-
oriented labor relations.
Kohl and Platzer (2004) also present data that are largely consistent with Visser’s. The
ranking of countries is identical with the exception of the Czech Republik, which has a higher
coverage rate of bargaining as well as a higher union density. In the summary index the Czech
Republic would thus be close to Hungary and above Poland. Kohl and Platzer emphasize that
labor relations are still in process of unfinished formation and tentatively suggest grouping the
countries into Northern and Southern CEECs. The latter group (Slovenia, Slovakia, and
Hungary) would thus be moving toward Germanic labor relations, whereas the Northern
countries (Czech Republic, Poland, and Lithuania) would be closer to disorganized labor
relations.
The ranking has to be interpreted with caution. First, we lack comparable time-varying data
on the degree of coordination of wage bargaining. The most reliable data (i.e. Visser 2004)
refers to the end of our period. Second, the ranking is dependent on the measure used.
Visser’s index by design strongly depends on the measure of collective agreement coverage.
Union membership would suggest a similar ranking, but with a different position for Czech
Republic. Third, qualitative research on labor relations fails to find evidence for strong
differences among these countries (Pollert 2000).
10
Data and stylized facts
The effects of national and sectoral factors in wage formation will be investigated by means
of sectoral panel regression within each country. The main database is the Vienna Institute for
International Economic Studies (WIIW) Industrial Database, 1-digit level sectoral data (ISIC
Rev. 3, 14 sectors). Our sample covers only manufacturing, which is the only sector with
reliable and long time series data for wages and productivity at detailed sectoral classification.
Appendix A lists the names of the sectors. The countries under investigation are the New
Member States (NMS) in Central and Eastern Europe (CEE), for which data is available, that
is the Czech Republic, Hungary, Poland, Slovakia, Slovenia, and Lithuania. The other two
Baltic countries, Estonia and Latvia, could not be included due to data problems. To check
robustness some estimations are replicated on the 2-digit level (23 sectors), however this data
is only available for Slovenia, Hungary, Poland and Lithuania.
Data problems plague quantitative research on CEECs. Unfortunately for Lithuania no wage
data for sector 23 (Coke, refined petroleum products, nuclear fuel) is available and sector 16
(Tobacco products) is missing. While the latter is a minor problem, the former sector has a
strong effect in several countries, since it usually is the highest paying manufacturing sector.
Thus all relevant regressions will be reported in two forms: first with the full sample. This
version is preferable for the comparison between Slovenia, Slovakia, Hungary, Poland and the
Czech Republic, but is not comparable between Lithuania and the other countries. A second
reduced sample, excluding sectors 23 and 16 (15 &16 at the 1-digit level) will be reported to
allow comparisons between Lithuania and the other economies.
All countries display a rising trend in manufacturing wage disparity, with a strong difference
11
in the levels of disparity. Table 2 summarizes the variation coefficients, i.e. the standard
deviation over the mean, for the real wage level (deflated by CPI). The first measure of wage
disparity, the full measure of variation coefficients including all available sectors (Table 2.1),
is only comparable between Slovenia, Slovakia, Hungary, Poland and the Czech Republic, but
incomparable with Lithuania. According to this measure Slovenia (23.1 in 2004) and the
Czech Republic (22.7) have the lowest levels of wage disparity. Slovakia (37.5) and Poland
(36.8) have intermediate levels and Hungary (50.6) has substantially higher levels of wage
disparity. In all countries wage disparity increased steadily, in Slovakia and Hungary this
increase accelerated since 2000.
A second measure excludes sectors 15 & 16 and 23 and is therefore comparable also with
Lithuania, while the first measure is clearly preferable for comparisons within the other
countries. This is summarized in Table 2.2. In 2000 the Czech Republic had the lowest level
of disparity (18.3), followed by Slovakia (20.6) and Slovenia (22.9). Hungary has the highest
level of wage disparity (30.3). Lithuania (25.9) and Poland (24.2) have intermediate levels.
Thus the results are similar between the two measures but not identical. Slovenia, Slovakia
and the Czech Republic are characterized by low disparities, Poland and Lithuania by
intermediate levels and Hungary has high levels of wage disparity. Data at the two digit
levels, available only for four countries confirm this finding (Tables 2.3 and 2.4).
Table 2. about here
Wage growth (in manufacturing) has clearly lagged behind productivity growth in all
countries (Table 2.5). Productivity (in the total economy) grew dramatically since 1995, with
compound annual growth rates ranging from 3.4% (Slovenia) to 10.4% (Hungary). However,
it must be kept in mind that these rates exclude the painful transition crisis. Wages grew at a
12
much more modest rate of 2.5 (Slovenia) to 4.7 (Lithuania, 1995-2001), resulting in a
substantial decline in the wage share in all CEECs. In 2000, the middle of our period of
observation, Slovenia and the Czech Republic had the highest per capita GDP, Slovakia,
Hungary and Poland medium levels and Lithuania had the lowest per capita GDP.
Regression results
The stylized facts on wage dispersion are suggestive, but they cannot take into account the
shocks that affect sectoral wages. Therefore we turn to regression analysis. Here sectoral
shocks, such as technology shocks, will be reflected by sectoral labor productivity. The effect
of average wages of the total economy, which also include services, are used as to gauge the
effective coordination of bargaining.**
The regression to be estimated takes the form
tjjttjtjt aCbwtbxbw
ε
+
+
+
+
=321 )log()log()log(
where w, x and wt are the sectoral real wage (deflated by the CPI), sectoral output per
employee†† and total average wages respectively. C stands for other (sectoral) control
variables that will be added in further specifications. Subscripts j refers to sectors and
subscripts t to time. All specifications are estimated with sectoral fixed effects (aj) and
standard errors that are robust to serial correlation and cross section heteroscedasticity. Due to
the limited number of observations dynamic panel methods are not advisable. However, the
results to be presented are roughly consistent with analog specifications in difference form.
The inclusion of the national wage conflicts with the inclusion of fixed time effects, which
thus could not be included.
** Since we control for national wage, controlling for (national) unemployment rates is redundant because its
effects are presumably included in former.
†† This variable will also be referred to as labor productivity. Note that this is a measure of gross productivity,
not value added per employee. However, in a time series context one would expect them to behave similarly.
13
The linear wage compression hypothesis would expect a low (high) value for b1 and a high
(low) value for b2 if the country’s labor relations are highly (weakly) organized and
coordinated. In other words, we expect strong national effects, but weak sectoral effects in
coordinated labor markets. The U-shaped effects of labor relations hypothesis would expect
low values for b1 and high values for b2 for highly organized/ coordinated and dis-organized
labor relations, but a high b1 and a low b2 for intermediate levels of organization in labor
relations, with low degree of coordination. According to this hypothesis, both highly
organized and disorganized will generate the same outcome, that is, strong national effects
and low sectoral effects. The mechanisms that ensure the uniform national wage, however,
differ. In the case of highly organized labor relations, wage setting is coordinated
intentionally, whereas in the case of disorganized labor relations labor mobility ensures that a
uniform national wage prevails.
Table 3 summarizes the regression results. Again two sets of results are reported, once with
all sectors (table 3.1), once with a reduced set of sectors (3.2) to allow comparability with
Lithuania. The ordering of coefficients with respect to the national wage is the same in both
variants. Slovenia and the Czech Republic both have values of 0.9 or higher for the full
sample of sectors, and have the highest value in the reduced sample (1 and 0.86 respectively).
Slovakia (0.69 in Table 3.2), Hungary (0.66) and Lithuania (0.65) have intermediate values
around 0.66. Poland has substantially lower values in both specifications (0.4 in 3.2). The
effect of sectoral productivity on wages is consistently weak and is statistically insignificant
in the Czech Republic. The value is highest in Lithuania (0.22 in Table 3.2), followed by
Slovakia (0.16) and Hungary (0.11). In Poland (0.1) and Slovenia (0.09) it is close to 0.1 .
Insert Table 3.
14
The results at the 2-digit level (not available for the Czech Republic and Slovakia) are
summarized in Table 4.1 and 4.2. Both Slovenia and Lithuania have coefficients for total
(average) wages close to unity. Both Hungary and Poland have substantially lower values.
The effect of sectoral productivity is again consistently small though statistically significant.
Slovenia and Hungary have the lowest values (both 0.06 in Table 4.2), Lithuania has a
medium small value of 0.11, whereas Poland has the highest value of 0.19. The results in the
2-digit estimations are thus similar for Slovenia, Hungary, and Poland, but somewhat different
for Lithuania, which now has a higher value for the effect of total wages. (It has to be kept in
mind that Lithuania has a smaller sample since data is only available until 2001.) Poland’s
role as an outlier is confirmed.
All of the countries in our sample belong to the group of what King and Szelényi (2005)
called “capitalism from without”-transition countries. By this term they signify that in the
transition to capitalism in all these countries outward orientation played a paramount role in
establishing capitalist structures, whereas the ‘indigenous’ capitalist class plays a minor role
(economically), being mostly restricted to small and medium-sized enterprises. While not all
analysts would agree with King and Szelényi’s analysis, the central role of multinational
corporations and foreign direct investment (FDI) can hardly be disputed. Thus the question
arises, what, if any, the effect of FDI inflows and outward orientation on wage formation is.
To check for robustness a specification including the openness of the sector (in terms of
exports and imports relative to its output) and the (lagged) level of FDI stock (relative to
output of the sector) were included in the regression. Both factors may affect sectoral wages
and have figured prominently in analyses of the effects on relocation. Openness and FDI may
affect the labor intensity of production and shift real earnings in favor of labor according to
traditional trade theory. The abundant factor, here labor, ought to benefit. Conversely,
15
increased exposure to international trade may decrease the bargaining power of labor and thus
shift the wage curve downwards. FDI inflows may also be a two-edged sword. The threat
effects of FDI, which is presumably more sensitive to wage costs than domestic investment,
may affect the slope of the bargaining curve. The overall effects of FDI and openness are thus
theoretically ambiguous (Onaran and Stockhammer 2006).
Insert Table 4. about here
The inclusion of FDI and Openness affects the sample size, since import and export data only
starts in 1999 and FDI data is not available for all sectors in Poland. Moreover FDI data is
only available at the 1-digit level. The results are thus not strictly comparable with the above.
Sectoral openness has a statistically significant negative effect on (sectoral) wages in Poland
and in the Czech Republic and no statistically significant effect elsewhere. FDI stock (relative
to output) has a statistically significant positive effect in Slovenia and Slovakia, but a
statistically significant negative effect in the Czech Republic and a negative effect (at the 10%
level) in Poland. However this latter is not comparable to the other countries since the sample
is reduced by one third due to a lack of FDI data. It is remarkable that the effect of FDI is
positive in Slovenia and Slovakia, which have been relatively more cautious in opening up,
whereas Poland and the Czech Republic, both once poster children of rapid liberalization,
have negative effects of FDI. Given problems of data quality and the short sample the
regression results have to be interpreted with caution. Together with the finding that openness
has no or negative effects, the results suggests that at least for labor it may be advantageous to
have a government that liberalizes cautiously.
Coming back to the robustness of the effect of average wages in these new specifications, the
results confirm the strong effect in Slovenia and Czech Republic and indicate intermediate
16
effects in Hungary, Lithuania and Slovakia. In Poland the sign becomes statistically
significantly negative. This latter has no economic interpretation, but confirms that Poland is
an outlier. Poland and Lithuania show a relatively strong effect of sectoral productivity
(though in the case of Lithuania not statistically significant), Slovenia, Hungary and Slovakia
show (statistically significant) moderate effects (0.16, 0.16 and 0.13 respectively). For the
Czech Republic there seems to be no effect.
Table 5 about here
The sectors included in our analysis differ among other things in their capital intensity and in
the amount of skilled and unskilled labor they use. Wage formation may also differ along
these dimensions and not only across countries. Therefore the sectors were disaggregated into
three groups: capital-intensive and skilled (CS) sectors, capital-intensive and unskilled (CU)
sectors and labor-intensive and unskilled (LU) sectors.‡‡ The regressions analysis was
performed for these groups and results are reported in table 6. The sector groups only contain
three to five sectors, however the precision of coefficient estimates does not deteriorate as
standard errors are not larger than in previous specifications. The effect of national wages is
statistically significant in all cases and the effect of sectoral productivity is statistically
significant in more than two thirds of the cases, with some statistically insignificant or
perverse signs (in Slovenia and Poland), all of which occurred in unskilled sectors. CS sectors
have higher coefficient estimates for the effect of national wages than other sectors in all
countries except Lithuania. In most countries CU sectors have stronger effects of national
wages than LU sectors in most countries, but not in Hungary and the Czech Republic (in
Poland the coefficient estimate is very similar). The pattern in the size of the effect of sectoral
productivity is less clear. In most countries (but not Poland and Lithuania) CU sectors have
‡‡ A forth group, labor-intensive and skilled consisted only of one sector and was hence dropped from the
regression analysis.
17
the strongest effect of sectoral productivity. In all countries except Lithuania is the coefficient
higher in CS than in LU sectors, the latter coefficient being statistically insignificant (at the
5% level) or negative in four cases.
Table 6 about here
As regards wage formation along skill and capital intensity Lithuania seems to differ from the
other countries. However the results for Lithuania are not strictly comparable with the rest
since data on sector 23 is missing, which as noted earlier, is a sector with high and
dynamically growing wages. But our findings may also reflect the fact that unskilled sectors
play a more central role the Baltic countries than in the Visegrad countries (Bohle and
Greskovits 2005).
Overall it seems that capital-intensive, skilled sectors have the strongest national factors in
wage formation, and labor-intensive, unskilled sectors the weakest. A simple explanation
(involving inverse causation) is that capital-intensive, skilled sectors are the leading sectors in
a system of pattern bargaining. Sectoral productivity effects are strongest in capital-intensive,
unskilled sector and weakest in labor-intensive, unskilled sectors. This may be explained by
the higher organizational level and thus bargaining power of workers in large scale, capital
intensive firms. Also capital intensive sectors are the ones, where there is more scope for
sharing of the oligopoly rents. Sectors clearly differ within countries in the wage formation.
However, the order of magnitude of the coefficient estimates does not change ordering of
countries as previously established.
18
Conclusion
The aim of the paper was to explore the relative role of sectoral and national factors in wage
formation in CEECs. In the context of Western OECD countries it is widely accepted that the
degree of organization of labor relations, that is the existence of centralized and/or
coordinated wage bargaining, leads to wage compression. Alternatively, one can reason that a
very competitive setting, i.e. dis-organized labor relations, may yield identical outcomes since
a uniform wage will be enforced by market pressures throughout the sectors of the economy.
Labor relations have only recently emerged in Eastern Europe. Consequently there is little
research (available in English) on wage formation. The countries offer a significant degree of
variation in labor relations, despite the fact that labor relations are still in the process of
development. Slovenia, “the Sweden of the East”, and to a lesser extent Slovakia have a
highly organized labor relations, whereas Lithuania has disorganized ones. Hungary, Poland,
and the Czech Republic, take intermediate places, according to a classification by Visser
(2005) in descending order.
Wage regressions were estimated for Slovenia, Slovakia, Hungary, Poland, the Czech
Republic and Lithuania for a panel of manufacturing sectors. Sectoral wages were explained
by average national wages and sectoral productivity. The effect of sectoral productivity was
mostly modest, whereas sectoral wages are strongly linked to national wage movements. The
regression results indicate that Slovenia and the Czech Republic show the strongest national
component in wage movements, with minor, if any, effects from sectoral productivity.
Slovakia, Hungary, and Lithuania form another group, with substantially weaker national
effects and stronger sectoral ones. The ordering between the three with respect to the national
component is sensitive to the specification. Lithuania and Poland consistently have the
19
strongest sectoral effects in wage formation. Poland seems to be an outlier. It consistently has
the weakest national effects and the strongest sectoral effects.
Any interpretation of the relation between the regression results and the labor relations has to
proceed with caution. There are various problems with the comparability of the data
(including different samples for Lithuania). Morevoer, the ranking of the degree of
organization of wage bargaining refers to the end of the period of investigation. Lack of
accurate data precludes the development of time-varying indices of the degree of
coordination, despite the fact that the changes over time were dramatic.
The ordering of the coefficients in the individual countries bears little resemblance with
Visser’s index of coordination of wage bargaining. Our findings are also pointing in a
different direction than Kohl and Platzer’s grouping of countries in Northern and Southern
CEEC labor relations. The ranking of the coefficients, however, are roughly consistent with
the ranking according to union densities. As a summary of the results a scatter plot of the
coefficient estimates for the effect of national wages on sectoral wages (based on Tables 3.2
and 5) and Visser’s coordination index is drawn in Figure 1.
Insert Figure 1
There are several possible interpretations of our results. First, they may be interpreted as weak
support for a u-shaped relation between the degree of centralization of collective bargaining
and the wage spread: Slovenia and Czech Republic lying on the one extreme, Poland at the
other. The polynomic trend line of second order in Figure 1 clearly suggests a u-shaped
relation. The small number of countries does not allow for further statistical analysis.
However, the u-shaped finding clearly rests on the results for the Czech Republic.
20
The second interpretation is that Visser’s index of coordination is misleading in our context
and that union density is a better measure of effective coordination. Figure 2 plots of the
coefficient estimates for the effect of national wages on sectoral wages (as in Figure 1) against
union density (based on Visser as summarized in Table 1). The ranking of the coefficients on
the impact on national factors in wage bargaining is in line with the ranking in terms of union
density. Morever, polynomic trends of second order have been added, which clearly indicate a
monotonous relation between union density and the effect of national wages on sectoral
wages. In the context of mostly firm-level bargaining the organizational strength (and
potentially the political fragmentation) of unions may be the most important factor
determining effective wage coordination.
Figure 2
A third interpretation is suggested by the fact that per capita GDP and the impact of national
factors in wage setting seem to be positively correlated. Slovenia and the Czech Republic are
the most developed among the countries discussed and have the strongest effects of national
wages on sectoral wages. Lithuania and Poland, which have the lowest GDP per capita, have
the weakest effect of national wages. This is thus what we might call a Kuznets effect, even
though such a label would not be entirely accurate: Kuznets (1955) original finding that
inequality decreases with per capita income referred to a development over time, whereas our
argument refers to differences across countries.
What has become clear is that generalizations from Western experience to the CEECs can, at
least in the case of the relation between wage spread and bargaining structures, be misleading.
The limitations of this study suggest several questions for future research. First, more research
21
in the nature of labor relations is needed. In particular the explicit and implicit role of labor
unions in wage coordination should be investigated. Second, future research on the effects of
wage coordination on wage formation should take into account different skill levels explicitly.
Third, the nature of shocks has been taken for granted in this study. Identifying these shocks
and analyzing their differences across countries may shed new light on how bargaining
institutions cope with shocks.
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23
Tables
Table 1. Indicators on national labor relations
summary
index of
coordination centralization
dominant
level of
bargaining union density CB coverage
minimum
wage %
avgerag
e income
year 2003 2003 2003 2002 2000 1999-
2001 2002 2000 2001
Source Visser Visser Visser K&P A&D Visser K&P
Schroed
er
Slovenia 0.63 0.43 NS 41 42 100 98 52
Slovakia 0.28 0.33 SF 35.4 35 40 40 48 41
Hungary 0.28 0.26 F 19.9 25 20 40 42 40
Poland 0.21 0.2 F 14.7 18 15 40 30- 38
Czech R 0.16 0.27 F 25.1 30 30 27.5 35 33
Lithuania 0.11 0.23 F 16 14 10 13 42
Sweden 0.57 0.56 S 78 90+
Austria 0.54 0.71 S 35.4 98.5
Germany 0.43 0.47 S 23.2 70
France 0.37 0.17 F 9.7 90
UK 0.17 0.13 F 30.4 40-
Note: in (4) national (N), sectoral (C), and firm (F)
Sources: Visser (2004), Kohl and Platzer (2004), Aguillera and Dabu (2005),
Schroeder (2002)
24
Table 2. Wage spread and wage increases in CEECs
2.1. Coefficients of variation of real wages, 1-digit
Slovenia Slovakia Hungary Poland Czech
Republic Lithuania
a
1995 22.9% 24.7% 33.9% 33.0% 15.50%
2000 21.0% 25.1% 41.1% 33.4% 21.56%
2004 23.1% 37.5% 50.6% 36.8% 22.68%
2.2. Coefficients of variation of real wages, 1-digit, without sectors 15&16 and 23
Slovenia Slovakia Hungary Poland Czech
Republic Lithuania b
1995 20.5% 18.3% 24.9% 18.9% 14.13% 25.42%
2000 22.9% 20.6% 30.3% 24.2% 18.31% 25.87%
2004 25.0% 22.2% 30.1% 26.2% 18.31%
2.3. Coefficients of variation of real wages, 2-digit
Slovenia c Slovakia Hungary Poland Czech
Republic Lithuania
b
1995 30.71% 38.64% 33.00%
2000 29.03% 42.88% 37.59%
2004 30.51% 49.27% 36.84%
2.4. Coefficients of variation of real wages, 2-digit, without sectors 16 and 23
Slovenia c Slovakia Hungary Poland Czech
Republic Lithuania b
1995 29.84% 32.59% 28.86% 37.88%
2000 28.78% 33.05% 32.36% 33.83%
2004 29.69% 33.09% 32.96%
2.5. GDP per capita 2000 and compound annual % change in the real wage and productivity (1995-
2004)
Slovenia Slovakia Hungary Poland Czech
Republic Lithuania b
GDPpc 2000 16340 10690 11900 10200 14590 8654
Labor
Productivity 3.4% 8.3% 10.4% 10.0% 7.2% 8.9%
Real wage 2.8% 2.5% 3.8% 2.7% 4.1% 4.7%
a) Series ends in 2001 and does not cover Sector 23 and sector 16
b) Series ends in 2001
c) begins 1997, ends 2003
25
Table 3.1. Sectoral wages 1. Digit incl. all sectors
Slovenia Slovakia Hungary Poland Czech
Republic Lithuania
X 0.104 0.178 0.121 0.062 0.024
t-Stat 9.701 6.719 2.939 1.709 1.098
WT 0.913 0.709 0.714 0.515 0.901
t-Stat 40.874 9.470 10.120 4.442 12.033
sectoral FE yes yes yes yes yes
MDV 11.892 9.316 11.277 7.378 9.424
R2 0.984 0.971 0.985 0.986 0.976
F 521.094 273.688 547.916 589.548 331.066
Obs 140 140 140 140 140
Sample 1995:2004 1995:2004 1995:2004 1995:2004 1995:2004
sectors 14 14 14 14 14
Table 3.2. Sectoral wages 1-digit without sectors 15&16 and 23
Slovenia Slovakia Hungary Poland Czech
Republic Lithuania
X 0.086 0.158 0.113 0.097 0.021 0.226
t-Stat 8.411 7.949 3.414 2.802 0.997 5.637
WT 0.999 0.686 0.663 0.400 0.863 0.648
t-Stat 32.062 7.813 12.617 2.662 13.435 8.992
sectoral FE yes yes yes yes yes yes
MDV 11.864 9.277 11.214 7.331 9.397 6.723
R2 0.990 0.981 0.988 0.980 0.983 0.957
F 844.714 426.785 683.854 401.746 462.173 121.242
Obs 120 120 120 120 120 84
Sample 1995:2004 1995:2004 1995:2004 1995:2004 1995:2004 1995:2001
sectors 12 12 12 12 12 12
26
Table 4.1. Sectoral wages 2-digit incl. all sectors
Slovenia Hungary Poland Lithuania
X 0.082 0.056 0.136
t-Stat 4.661 2.526 3.664
WT 0.947 0.653 0.431
t-Stat 32.454 6.128 4.659
sectoral FE yes yes yes
MDV 11.934 11.316 7.441
R2 0.983 0.954 0.969
F 332.8 175.4 264.6
Obs 161 230 230
Sample 1997:2003 1995:2004 1995:2004
sectors 23 23 23
Table 4.2. Sectoral wages 2-digit without sectors 16 and 23
Slovenia Hungary Poland Lithuania
X 0.060 0.060 0.186 0.114
t-Stat 2.504 2.603 3.457 3.479
WT 0.945 0.590 0.232 0.947
t-Stat 26.258 5.929 1.824 13.056
sectoral FE yes yes yes yes
MDV 11.910 11.250 7.386 6.741
R2 0.986 0.947 0.963 0.843
F 384.5 151.2 220.9 30.0
Obs 147 210 210 147.00
Sample 1997:2003 1995:2004 1995:2004 1995:2001
sectors 21 21 21 21
27
Table 5. Wage regression including FDI and openess (1-digit level)
Slovenia Slovakia Hungary Poland Czech
Republic Lithuania
X 0.155 0.131 0.155 0.190 0.000 0.190
t-Stat 3.696 5.863 5.363 4.265 -0.197 1.549
WT 0.801 0.291 0.503 -0.332 0.836 0.404
t-Stat 9.862 2.029 15.184 -2.155 40.762 0.567
FDI 0.104 0.191 0.046 -0.198 -0.091 0.178
t-Stat 2.238 3.418 0.989 -1.771 -7.746 0.705
Openness 0.002 -0.038 0.019 -0.008 -0.004 0.006
t-Stat 0.272 -1.716 1.073 -0.249 -2.008 0.690
MDV 11.916 9.313 11.296 7.415 9.462 6.830
R2 0.995 0.988 0.995 0.995 0.997 0.985
F 723.6 320.8 806.1 641.2 1329.0 90.2
Obs 72 72 72 48 72 36
Sample 1999:2003 1999:2003 1999:2003 1999:2003 1999:2004 1999:2001
sectors 12 12 12 8 12 12
28
Table 6. Wages formation according to skill and capital intensity (1-digit level)
CS CU LU CS CU LU
Slovenia Slovakia
X 0.115 0.189 -0.102 X 0.215 0.229 0.118
t-Stat 7.672 4.249 -1.833 t-Stat 13.682 11.004 11.985
WT 1.071 0.788 0.610 WT 0.812 0.764 0.575
t-Stat 20.919 14.212 4.073 t-Stat 5.934 5.647 4.755
MDV 12.058 11.887 0.969 MDV 9.511 9.456 9.052
R2 0.973 0.929 7.070 R2 0.921 0.942 0.959
Obs 50 30 50 Obs 50 30 50
Sample 1995:2004 1995:2004 1995:2004 Sample 1995:2004 1995:2004 1995:2004
sectors 5 3 5 sectors 5 3 5
Hungary Poland
X 0.172 0.341 0.099 X 0.064 -0.026 -0.102
t-Stat 4.542 5.012 1.717 t-Stat 2.753 -0.484 -1.833
WT 0.771 0.479 0.635 WT 0.809 0.595 0.610
t-Stat 9.531 4.746 9.337 t-Stat 21.869 3.372 4.073
MDV 11.600 11.308 10.920 MDV 7.654 7.386 7.070
R2 0.967 0.961 0.978 R2 0.990 0.802 0.969
Obs 50 30 50 Obs 50 30 50
Sample 1995:2004 1995:2004 1995:2004 Sample 1995:2004 1995:2004 1995:2004
sectors 5 3 5 sectors 5 3 5
Czech
Republic Lithuania
X 0.102 0.175 0.002 X 0.350 0.173 0.124
t-Stat 2.243 8.312 0.224 t-Stat 7.350 2.942 3.597
WT 0.972 0.611 0.732 WT 0.449 0.863 0.583
t-Stat 7.224 11.831 22.803 t-Stat 4.589 5.385 6.918
MDV 9.605 9.485 9.205 MDV 6.954 6.676 6.550
R2 0.941 0.980 0.976 R2 0.947 0.896 0.956
Obs 50 30 50 Obs 28 21 35
Sample 1995:2004 1995:2004 1995:2004 Sample 1995:2001 1995:2001 1995:2001
sectors 5 3 5 sectors 4 3 5
CS = capital and skill intensive sectors
CU = capital intensive and unskilled sectors
LU = labor intensive and unskilled sectors
29
Figure 1
Coordination of wage bargaining and the effect of national wages on sectoral wages
0,00
0,20
0,40
0,60
0,80
1,00
1,20
0 0,1 0,2 0,3 0,4 0,5 0,6 0,7
Specification 1
Specification 2
Polynomic trend 1
Polynomic trend 2
Czech Republic
Note: The effect of national wages on sectoral wages are the coefficient estimates from Table
3.2 (“specification 1”) and Table 5 (“specification 2”). The trend lines are the polynomic
trends of second order for the scatter plots based on specification 1 and 2 respectively. The
statistically insignificant negative coefficient estimate for Poland in specification 2 is treated
as zero. Data on the index of wage coordination is taken from Table 1.
30
Figure 2
Union density and the effect of national wages on sectoral wages
0,00
0,20
0,40
0,60
0,80
1,00
1,20
10 15 20 25 30 35 40 45
Specification 1
Specification 2
Polynomic trend 1
Polynomic trend 2
Note: The effect of national wages on sectoral wages are the coefficient estimates from Table
3.2 (“specification 1”) and Table 5 (“specification 2”). The trend lines are the polynomic
trends of second order for the scatter plots based on specification 1 and 2 respectively. The
statistically insignificant negative coefficient estimate for Poland in specification 2 is treated
as zero. Data on union density is taken from Table 1.
31
Appendix
A.1 Data definitionas and sources
Variable Definition Source
W average monthly gross wages, real WIIW Industrial Database Eastern
Europe
X (gross) output per employee WIIW Industrial Database Eastern
Europe
WT average monthly gross wages, real WIIW Handbook of Statistics
FDI inward FDI stocks (iip) as percentage of
output
WIIW Database on Foreign Direct
Investment
Openness imports and exports from and to the world
as percentage of output
WIIW Industrial Database Eastern
Europe
GDP pc GDP per head ($ at PPP) EIU country data
A.2 List of the sectors
NACE rev. 1 divisions, identical to 2-digit level of ISIC rev. 3 code
(23 industries)
15 Food products and beverages
16 Tobacco products
17 Textiles
18 Wearing apparel; dressing and dyeing of fur
19 Tanning and dressing of leather; related articles
20 Wood and products of wood and cork
21 Pulp, paper and paper products
22 Publishing, printing and reproduction of recorded media
23 Coke, refined petroleum products, nuclear fuel
24 Chemicals and chemical products
25 Rubber and plastic products
26 Other non-metallic mineral products
27 Basic metals
28 Fabricated metal products, except machinery and equipment
29 Machinery and equipment
30 Office, accounting and computing machinery
31 Electrical machinery and apparatus
32 Radio, TV & communication equipment and apparatus
33 Medical, precision, optical instruments, watches and clocks
34 Motor vehicles, trailers and semi-trailers
35 Other transport equipment
36 Furniture; manufacturing n.e.c.
37 Recycling
32
1 digit
15-16: food products, beverages and tobacco products 1
17-18: textiles and textile products 2
19: Tanning and dressing of leather; manufacture of luggage,
handbags, saddlery, harness and footwear
3
20: wood and of products of wood and cork, except furniture;
manufacture of articles of straw and plaiting materials
4
21-22: Pulp, paper, paper products, printing and publishing 5
23: coke, refined petroleum products and nuclear fuel 6
24: chemicals and chemical products 7
25: rubber and plastics products 8
26: other non-metallic mineral products 9
27-28: basic metals and fabricated metal products 10
29: machinery and equipment n.e.c. 11
30-33: electrical and optical equipment 12
34-35: transport equipment 13
36-37: Manufacture n.e.c., Recycling 14
A.3 Taxonomy of sectors with respect to capital intensity and skill
1 digit
CS LS CU LU
21-22 30-33 25 15-16
23 26 17-18
24 27-28 19
29 20
34 35 36-37
33
A.4 Descriptive statistics
1-Digit
incl. all
sectors
without
sectors
15&16 and 23
WR WRP X WRT WR WRP X WRT
SLO
Mean 14.377 14.364 16.095 14.552 14.349 14.338 16.015 14.346
Std. Dev. 0.210 0.232 0.551 0.068 0.212 0.207 0.480 0.238
SLK
Mean 11.801 11.752 14.094 11.748 11.762 11.756 13.917 11.748
Std. Dev. 0.264 0.336 0.825 0.044 0.233 0.324 0.659 0.044
HUN
Mean 13.762 13.809 16.000 13.801 13.699 13.764 15.879 13.801
Std. Dev. 0.372 0.368 0.782 0.139 0.319 0.342 0.747 0.140
POL
Mean 9.863 9.771 11.892 9.894 9.816 9.733 11.732 9.894
Std. Dev. 0.301 0.374 0.675 0.097 0.257 0.357 0.503 0.097
CZ
Mean 11.909 11.987 14.193 11.970 11.882 11.965 13.987 11.970
Std. Dev. 0.225 0.248 0.775 0.108 0.211 0.239 0.493 0.108
LIT*
Mean 9.210 9.173 10.982 9.245 9.208 9.172 10.943 9.245
Std. Dev. 0.258 0.340 0.491 0.121 0.268 0.351 0.491 0.121
*series ends in 2001
2-Digit
incl. all sectors without sectors 16 and 23
WR WRP X WRT WR WRP X WRT
SLO**
Mean 14.419 14.364 16.040 14.566 14.394 14.366 15.993 14.566
Std. Dev. 0.210 0.249 0.622 0.044 0.200 0.255 0.589 0.044
HUN
Mean 13.801 13.832 16.042 13.664 13.735 13.856 15.937 13.664
Std. Dev. 0.360 0.386 0.847 0.140 0.293 0.392 0.807 0.140
POL
Mean 9.926 9.836 11.951 9.894 9.871 9.862 11.828 9.894
Std. Dev. 0.311 0.412 0.681 0.097 0.263 0.417 0.565 0.097
LIT*
Mean 9.206 7.389 10.943 7.167 9.206 7.224 10.943 7.167
Std. Dev. 0.272 0.497 0.596 0.121 0.272 2.388 0.596 2.410
*series ends in 2001
**series starts 1997 and ends 2003
WR real wage (CPI)
WRP real product wage (sectoral deflator)
QR (gross)output per employee
WRT real wage (CPI) in total economy
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1997.
Grandner T., Territoriale Evolution von Kooperation in einem Gefangenendilemma, No. 45, February 1997.
Häfke Ch., Sögner L., Asset Pricing under Asymmetric Information, No. 46, February 1997.
Stiassny A., Die Relevanz von Effizienzlöhnen im Rahmen von Gewerkschaftsverhandlungsmodellen, No.
47, May 1997.
Stiassny A., Unsicherheit bezüglich der Preiselastizität der Güternachfrage als reale Rigidität, No. 48, May
1997.
Klausinger H., Die Alternativen zur Deflationspolitik Brünings im Lichte zeitgenössischer Kritik, No. 49, June
1997.
Wehinger G.D., Exchange Rate-Based Stabilization: Pleasant Monetary Dynamics?. No. 50, August 1997.
Wehninger G.D., Are Exchange Rate-Based Stabilizations Expansionary? Theoretical Considerations and
the Brazilian Case, No. 51, August 1997.
Huber C., Sögner L., Stern A., Selbstselektierendes Strompreisregulierungsmodell, No. 52, August 1997.
Ragacs Ch., Zagler M., Economic Policy in a Model of Endogenous Growth, No. 53, October 1997.
Mahlberg B., Url T., Effects of the Single Market on the Austrian Insurance Industry, No. 54, February 1998.
Gstach D., Grander T., Restricted Immigration In as Two-Sector Economy, No. 55, March 1998.
Sögner L., Regulation of a Complementary Imputed Good in a Competitive Environment, No. 56, March
1998.
Altzinger W., Austria's Foreign Direct Investment in Central and Eastern Europe: 'Supply Based' or Marked
Driven?, No. 57, April 1998.
Gstach D., Small Sample Performance of Two Approaches to Technical Efficiency Estimation in Noisy
Multiple Output Environments, No. 58, June 1998.
Gstach D., Technical Efficiency in Noisy Multi-Output Settings, No. 59, June 1998.
Ragacs Ch., Zagler M., Growth Theories and the Persistence of Output Fluctuations: The Case of Austria,
No. 60, October 1998.
Grandner T., Market Shares of Price Setting Firms and Trade Unions, No. 61, October 1998.
Bellak Ch., Explaining Foreign Ownership by Comparative and Competitive Advantage: Empirical Evidence,
No. 62, March 1999.
Klausinger H., The Stability of Full Employment. A Reconstruction of Chapter 19-Keynesianism, No. 63, April
1999.
Katzmair H., Der Modellbegriff in den Sozialwissenschaften. Zum Programm einer kritischen Sozio-Logik,
No. 64, June 1999.
Rumler F., Computable General Equilibrium Modeling, Numerical Simulations in a 2-Country Monetary
General Equilibrium Model, No. 65, June 1999.
Zagler M., Endogenous Growth, Efficiency Wages and Persistent Unemployment, No. 66, September 1999.
Stockhammer E., Robinsonian and Kaleckian Growth. An Update on Post-Keynesian Growth Theories, No.
67, October 1999.
Stockhammer E., Explaining European Unemployment: Testing the NAIRU Theory and a Keynesian
Approach, No. 68, February 2000.
Klausinger H., Walras’s Law and the IS-LM Model. A Tale of Progress and Regress, No. 69, May 2000.
Grandner T., A Note on Unionized Firms’ Incentive to Integrate Vertically, No. 70, May 2000.
Grandner T., Optimal Contracts for Vertically Connected, Unionized Duopolies, No. 71, July 2000.
Heise, A., Postkeynesianische Beschäftigungstheorie, Einige prinzipielle Überlegungen, No. 72, August
2000.
Heise, A., Theorie optimaler Lohnräume, Zur Lohnpolitik in der Europäischen Währungsunion, No. 73,
August 2000.
Unger B., Zagler M., Institutional and Organizational Determinants of Product Innovations. No. 74, August
2000.
Bellak, Ch., The Investment Development Path of Austria, No. 75, November 2000.
Heise, A., Das Konzept einer nachhaltige Finanzpolitik aus heterodoxer Sicht – ein Diskussionsbeitrag, No.
76, April 2001.
Kocher M., Luptacik M., Sutter M., Measuring Productivity of Research in Economics. A Cross-Country
Study Using DEA, No. 77, August 2001.
Munduch, G., Pfister A., Sögner L., Stiassny A., Estimating Marginal Costs fort he Austrian Railway System,
No. 78, Februray 2002.
Stückler M., Überprüfung von Gültigkeit und Annahmen der Friedman-These für Rohstoffmärkte, No. 79,
July 2002.
Stückler M., Handel auf Terminkontraktmärkten, No. 80, July 2002.
Ragacs Ch., Minimum Wages, Human Capital, Employment and Growth, No. 81, August 2002.
Klausinger H., Walras’ Law in Stochastic Macro Models: The Example of the Optimal Monetary Instrument,
No. 82, November 2002.
Gstach D., A Statistical Framework for Estimating Output-Specific Efficiencies, No. 83, February 2003.
Gstach D., Somers A., Warning S., Output specific efficiencies: The case of UK private secondary schools,
No. 84, February 2003.
Kubin I., The dynamics of wages and employment in a model of monopolistic competition and efficient
bargaining, No. 85. May 2003.
Bellak Ch., The Impact of Enlargement on the Race For FDI. No. 86 Jan. 2004
Bellak Ch., How Domestic and Foreign Firms Differ and Why Does it Matter?. No. 87 Jan. 2004
Grandner T., Gstach D., Joint Adjustment of house prices, stock prices and output towards short run
equilibrium, No. 88. January 2004
Currie M., Kubin I., Fixed Price Dynamics versus Flexible Price Dynamics, No. 89, January 2005
Schönfeld S., Reinstaller A., The effects of gallery and artist reputation on prices in the primary market for
art: A note, No. 90, May 2005
Böheim, R. and Muehlberger, U., Dependent Forms of Self-employment in the UK: Identifying Workers on
the Border between Employment and Self-employment. No. 91, Feb. 2006
Hammerschmidt, A., A strategic investment game with endogenous absorptive capacity. No. 92, April 2006
Onaran, Ö., Speculation-led growth and fragility in Turkey: Does EU make a difference or “can it happen
again”? No. 93, May 2006
Onaran, Ö., Stockhammer, E., The effect of FDI and foreign trade on wages in the Central and Eastern
European Countries in the post-transition era: A sectoral analysis. No. 94, June 2006
Burger, A., Reasons for the U.S. growth period in the nineties: non-keynesian effects, asset wealth and
productivity. No. 95, July 2006
Stockhammer, E., Is the NAIRU theory a Monetarist, New Keynesian, Post Keynesian or a Marxist theory?
No. 96, March 2006
Onaran, Ö., Aydiner-Avsar, N., The controversy over employment policy: Low labor costs and openness, or
demand policy? A sectoral analysis for Turkey. No. 97, August 2006
Klausinger, H., Oskar Morgenstern als wirtschaftspolitischer Berater in den 1930er-Jahren. No. 98, July
2006
Rocha-Akis, S., Labour tax policies and strategic offshoring under unionised oligopoly. No. 99, November
2006
Stockhammer, E., Onaran, Ö., National and sectoral factors in wage formation in Central and Eastern
Europe. No. 100, December 2006
