Lithuania’s productivity is gaining, but pace could be faster

1. Swedbank Analysis May 30, 2011
Lithuania’s productivity is gaining, but pace
could be faster
 It took 13 years for Lithuania’s labour productivity to double – at
the beginning of 2008 value added per employee was two times
higher than in 1995. Despite this fast convergence, productivity is
still well below the EU average.
 Labour productivity in Lithuania grew faster than in the rest of
Europe, not only because of catching up, but also because of the
different structure of economies – Lithuania is much less de-
pendent on services, where the growth of productivity is slower.
Furthermore, the structure of the economy is changing as the
country slowly crawls upwards the value-added chain.
 Labour productivity, unsurprisingly, is very uneven across differ-
ent sectors. Some manufacturers have converged rapidly to-
wards the EA average, whereas others are less productive than
they were a decade ago.
 Value added per employee depends on many factors, and most
are difficult to quantify. Accumulated capital explains a big part of
the differences in labour productivity, but other important factors
are education, organizational efficiency and culture, the institu-
tional and political environment, corruption, and the judicial sys-
tem – all of which need improvement.
Labour productivity is converging rapidly
Labour productivity measures the amount of goods and services pro-
duced per each member of the labour force or per hour worked. It is one
of a country’s most important indicators of economic progress. However,
it is influenced by many different, and sometimes nonmeasurable, factors
that go beyond employee’s competencies and capital with which they op-
erate. Thus, it is important to understand what drove Lithuanian produc-
tivity growth in the past decade and whether similar trends can be ex-
pected in the future.
Lithuanian labour productivity was among the fastest growing in the re- In the past decade, la-
gion – in 2008, before the global financial crisis and economic recession, bour productivity growth
it was 60 percent higher than in 2000 and twice as large as in 1995. In was among the fastest in
contrast, in the pre-crisis period, Estonian productivity was increasing the region.
slightly more slowly, but recovered faster after the recession.
Economic Research Department.
Swedbank AB. SE-105 34 Stockholm. Phone +46-8-5859 1000
E-mail: ek.sekr@swedbank.com www.swedbank.com
Legally responsible publisher: Cecilia Hermansson, +46-8-5859 7720
Nerijus Mačiulis + 370 5 258 2237. Lina Vrubliauskienė +370 5 258 2275

2. Real labour productivity per hour worked
(Index 2000=100)
160
150
Lithuania
140 Slov akia
130 Estonia
Hungary
120
Poland
110
Euro area (17)
100
90
80
70
1995 1997 1999 2001 2003 2005 2007 2009
Source: Eurostat
In 2009, labour productivity contracted by 8.5%, but most of the losses
were regained in 2010. The loss in productivity was caused by plummet-
ing demand and a contraction in output. The recovery however happened
due to a loss of jobs (employment contracted by more than 5%) – i.e.,
this was not a “good kind” of productivity growth, which is usually caused
by investments and improvement in human capital. However, this year
and the next productivity will be increasing along with higher employment.
One reason for the rapid productivity growth was a very low base – at the Despite rapid growth,
beginning of the last decade, Lithuanian productivity was only 18% of the Lithuanian real labour
euro area average. productivity is still less
than one- fourth of the
Real labour productivity per hour worked
(% of EA average)
euro area average.
27%
Estonia 23%
19%
23% 2010
Lithuania 21% 2005
18% 2001
20%
Latv ia 18%
14%
0% 5% 10% 15% 20% 25% 30%
Source: Eurostat
Although over the past 10 years real labour productivity per hour worked
has improved significantly in all three Baltic countries, there is still a lot of
catching up to do. Lithuania’s labour productivity is at 23% of the euro
area average, above Latvia’s (20%), but below Estonia’s (27%).
The difference is less striking when one compares labour productivity at
the purchasing power standard (PPS) – all three Baltic countries have
exceeded the EU average. Estonia’s productivity, at 65.5%, is closest to
the EU average, followed by Lithuania’s, at 57.3%, and Latvia’s, at
53.0%.
2 Swedbank Analysis • May 30, 2011

3. Labour productivity, based on PPS per employed person
(% of EU average)
140
120 114.3 112.8 109.9
100
80 Estonia
65.4 64.4 65.5
58.9 61.3 Latv ia
57.3
60 51.4 51.5 53.0
Lithuania
Sweden
40
20
0
2007 2008 2009
Source:Eurostat, Swedbank calculations
Normally, the compensation of employees should reflect their productiv-
Compensation of em-
ity, not price trends, as sometimes is the case. The compensation of
ployees should reflect
Lithuanian employees is only 51.1% of the EU average, i.e., convergence
in wages is lagging behind productivity. This is not the case for Estonia, productivity.
where compensation of employees is closer to the EU average than is
productivity. Naturally, this is not an ideal benchmark, since compensa-
tion of employees also differs across sectors. Furthermore, even within
the same sectors differences in capital intensity and innovation play a
role.
Annual compensation per employee, based on PPS
(% of EU average)
140
127.5 124.9
121.7
120
100
80 67.8 67.6
63.3 Estonia
53.5 56.1
60 50.1 52.8 49.7 51.1 Latv ia
Lithuania
40
Sweden
20
0
2007 2008 2009
Source:Eurostat, Swedbank calculations
In general, besides investments in fixed tangible assets and improve-
ments in human capital, the changing structure of the economy explains
most of the productivity gains.
Less agriculture, more manufacturing and services
Labour productivity growth has also been boosted by the changing struc- Albeit slowly, the Lithua-
ture of the economy. But the Lithuanian economy did not evolve along nian economy is moving
the classical textbook path of an agricultural economy becoming indus- up the value-added
trial and, in a later stage, moving into services. As part of the Soviet Un- chain.
ion, Lithuania was a semi-industrial economy, dominated by large, low-
value-added factories, some of which became obsolete and during the
past decade were replaced by smaller and more dynamic manufacturing
branches.
Swedbank Analysis • May 30, 2011 3

4. In 1995, agriculture created almost 10% of value added in the economy.
This dropped to 3.4% last year and will probably continue converging to-
wards the EU average of less than 2%. The share of manufacturing has
been pretty stable, fluctuating between 18% and 20%--above the EU av-
erage and similar to that of Sweden and Germany.
Structure of gross value added, current prices Manufacturing will
(per cent)
dominate for the time be-
100
ing, while agriculture’s
24.9 24.4 22.8 22.1 21.4 21.7 21.4 22.5 25.1 23.1
80
25.6
33.6 share shrinks.
10.2 10.4 10.5 11.5 12.1 13.0 13.4
10.3 10.2 14.3 13.7
60 12.3 13.4 13.4 12.7 12.7 12.7 12.8
12.2 12.2 15.2 23.2
13.8
16.4 17.1 17.5 17.4 17.5 17.3 16.7 16.7 17.1
40 16.9 17.1 6.8
6.0 5.9 6.3 7.1 7.2 7.5 8.8 10.2 11.1
3.7 4.1 4.7 4.4 4.0 10.0 6.4 5.7
4.1 3.5 3.3 3.1 3.7
20 3.9 6.3
19.3 19.9 18.7 19.3 20.9 20.8 2.4
20.1 18.6 18.1 16.4 18.2
14.9
6.3 5.5 5.4 5.0 4.7 4.8 4.3 3.9 3.7 3.4 3.4 1.7
0
2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 EU-27,
Agriculture, f ishing Manuf acturing 2009
Electricity , gas and water supply Construction
Wholesale and retail trade Transport, storage and communication
Real estate, renting and business activ ities Other
Source: Statistics Lithuania, Eurostat
The share of services, such as real estate, renting, and business activi-
ties has gradually been increasing, but remains below the EU average.
Transport, storage, and communication services, in particular, create al-
most one-sixth of value added in Lithuania and more than double the EU
average.
Hotels and restaurants, as well as financial intermediation, create, re-
spectively, 1.2% and 2.4% of value added in the economy. This share
has hardly changed in the past 10 years and remains half of the EU av-
erage.
Services in Lithuania make up only 68.7% of all the economy, compared
with an average of 74% in the EU. This is one reason why productivity
was converging faster – most services are usually considered as having
a low-growth productivity (there are a very limited number of haircuts you
can make in one hour). However, recent research1 shows that some de-
veloping economies – Pakistan, Sri Lanka, and India in particular – man-
aged to skip the manufacturing stage and moved straight to modern ser-
vices, such as software development, call centres, and outsourcing busi-
ness processes. These services use skilled labour, can exploit econo-
mies of scale, and can be exported (unlike traditional services, such as
catering or making haircuts). In the aforementioned countries, unlike in
Lithuania, the level of productivity is higher in services than in industry.
Should Lithuania continue relying on manufacturing or focus on modern Services sectors provide
services? A recently drafted long-term strategy (“Lithuania 2030”) implies possibilities…
the latter option should be taken. The current government has been very
active in attracting big international companies (Barclays, IBM, Western
Union, e.g.), all of which have invested in high-value-added services.
Lithuania is leading in many quantitative education indicators. In 2009, for
example, of the population aged 20-29, 87.8 out of 1,000 were university
graduates; this compares favourably with the average of around 60 in the
EU. The ratio of students to teacher is the lowest is Europe, two times
smaller than in Germany (indicating that more attention can be paid to
1
See, e.g. http://www.economist.com/node/18712351
4 Swedbank Analysis • May 30, 2011

5. each student). However, some of these high quantitative indicators sug-
gest that the education sector (dominated by public institutions) has not
been able to adjust and adapt to the dwindling population.
Good quantitative indicators are not reflected in an equally good outcome …but demand for skilled
of tertiary education. The latest results from the Programme for Interna- labour faces challenges
tional Student Assessment (PISA), coordinated by the OECD, show that due to the poor quality of
Lithuania is “statistically significantly below the OECD average.” On the higher education.
overall scale, Lithuania was ranked 40th, Latvia 30th, and Estonia 13th. On
the overall reading scale (considering the ability to access and retrieve,
integrate and interpret, and reflect and evaluate) Lithuania scored 468
points, below the OECD average of 493. On the mathematics and sci-
ence scale, Lithuanian students scored 477 and 491 points, below the
averages of 496 and 501, respectively.
Student performance in OECD, 2009
650
600
600
575
556
550
528
Ov erall reading scale
512
501
501
Mathematics scale
496
497
495
494
494
493
491
484
482
500
478
477
Science scale
468
468
459
450
400
OECD Shanghai Estonia Sweden Latv ia Lithuania Russia
av erage China (13th) (19th) (30th) (40th) (43rd)
(1st) Source: OECD, PISA
The recent higher education reform, which encourages competition
among universities, points in the right direction and over time will improve
the quality of education. Some of the problems (low motivation, lack of
critical thinking, valuing memorizing above understanding), however, be-
gin at the primary and secondary education levels and can hardly be re-
versed in universities. Reform should therefore begin at the core.
Productivity and its growth are different across the sectors
Productivity changes within different sectors were far from universal. Not all sectors improved
Over the last decade, the biggest productivity gains were recorded in their productivity in the
electricity, gas, and water supply, agriculture, and manufacturing. In this past decade.
period, many companies in the electricity, gas and water supply sector
were privatized by foreign capital, and all underwent significant renova-
tion and improved their efficiency – not least because the number of em-
ployees also declined by almost 30%. Like agriculture, this sector was
very unproductive to start with, and thus some of its rapid improvement is
explained by the very low base.
After accession to the EU, the agriculture sector received significant fi-
nancial support from different EU structural funds and thus was able to
significantly boost the productivity. Many small farms merged into bigger
conglomerates, allowing benefiting from economies of scale.
Swedbank Analysis • May 30, 2011 5

6. Value added per one employed person, 2010
(Index 2000=100)
Electricity , gas and water supply 243
Agriculture 234
Fishing 221
Manuf acturing 207
Transport, storage and communication 168
Trade 134
Public administration 130
Construction 120
Health and social work 109
Education 102
Financial intermediation 95
Hotels and restaurants 86
Real estate 73
Mining and quarry ing 73
50 75 100 125 150 175 200 225 250
Source: Eurostat
Manufacturing and transport, storage, and communication services were
EU support and FDI
the two sectors that attracted most foreign direct investments in the pre-
were important factors
vious decade; thus, their productivity improvement was also stellar.
behind productivity
Although productivity in the financial intermediation sector in 2010 was growth.
below its 2000 level, this was mainly because of the grave effects of the
financial crisis – labour productivity declined by 30% from the peak
reached in 2007. Another reason why this sector in Lithuania still has a
fairly low productivity (it is only 22% of the euro area average) is the still-
low penetration of financial services – the ratio of household loans to in-
come is among the lowest in EU, and, the number electronic transactions
(as opposed to circulation of cash) is lower only in Bulgaria and Romania.
Naturally, labour productivity is not equal across different sectors. In ab-
solute terms, it is highest in sectors where labour intensity is low – like
utilities or communication. Labour productivity is low in services sectors,
where economies of scale are hard to achieve – e.g., hotels and restau-
rants, education, and health and social work.
Value added per one employed person at constant prices
(thousands euros)
Electricity , gas and water
Transport, storage, comm.
Real estate
Mining and quarry ing
Manuf acturing
Public administration
Financial intermediation
Trade 2010
Construction 2000
Agriculture
Hotels and restaurants
Education
Fishing
Health and social work
0 5 10 15 20 25 30 35
Source: Statistics Lithuania, Swedbank calculation
Overall in the economy, value added per employee is equal to 27% of the
euro area average, ranging from 22% in the public sector and 37% in the
wholesale and retail trade, hotels and restaurants, and transport sector.
6 Swedbank Analysis • May 30, 2011

7. Lithuanian labour productivity per employee
(% of EA average)
Public administration and community serv ices 22%
Financial intermediation; real estate 22%
Agriculture; f ishing 23%
Total 27%
Construction 28%
Industry (except construction) 31%
Manuf acturing 32%
Wholesale and retail trade; hotels and
37%
restaurants; transport
0% 5% 10% 15% 20% 25% 30% 35% 40%
Source: Eurostat, Swedbank
Different branches of manufacturing have converged towards the euro
area average very unevenly. The biggest productivity increases were in
the highest-value-added manufacturing branches - machinery and
equipment, transport equipment, and electrical and optical equipment.
However, manufacturers of metals, rubber and plastic products, nonme-
tallic mineral products, and leather actually reduced labour productivity in
the past decade.
In 2008 and 2009, most manufacturing branches contracted sharply, due During the recession,
to the global financial crisis and economic recession in the entire region. output contracted more
Declining demand was followed by dropping productivity, because em- than employment.
ployment contracted slower than demand. Overall, gross value added in
manufacturing contracted by 15% in 2009, whereas employment dropped
by 12.3%.
Manufacturers of electrical and optical equipment were among the few
managing to increased productivity in both 2008 and 2009, not only both
because their output dropped by “only” 16%, but also because this sector
shed 22.4% of its jobs. In 2009, production of rubber and plastics
dropped by 20.6%, but employment increased by 28.2%, thus accounting
for the sharp drop in productivity. In retrospect, this jump in employment
was not too reckless, as demand for these products picked up very
quickly in 2010.
Labour productivity in manufacturing (per employee)
(Index 2000=100)
450
Manuf acturing, total
400
Ref ined petroleum products
350
Chemicals
300
Rubber and plastic products
250
Metals
200
Machinery and equipment
150
Transport equipment
100
Electrical and optical
50 equipment
2001 2002 2003 2004 2005 2006 2007 2008 2009
Source: Eurostat, Swedbank calculations
Swedbank Analysis • May 30, 2011 7

8. Currently, productivity in manufacturing of refined petroleum products, at Not all manufacturers
70%, is closest to the EA average. But this comes from just one com- managed to improve
pany, previously owned by US capital and now owned by one of the big- productivity faster than
gest refinery in Central and Eastern Euope– PKN Orlen. Productivity in the EA average.
manufacturing of electrical and optical equipment (45%) and transport
equipment (39%) has also converged towards the EA average. However,
producers of nonmetallic mineral products, leather, and chemicals are still
generating less than 20% of EA average.
Labour productivity in manufacturing (per employee)
(% of EA average)
Other non-metallic mineral products
Leather and leather products 2000
Chemicals 2009
Machinery and equipment n.e.c.
Textiles and textile products
Paper and paper products
Total
Wood and wood products
Metals and f abricated metal products
Food, bev erages and tobacco
Other
Transport equipment
Rubber and plastic products
Electrical and optical equipment
Ref ined petroleum products
0% 10% 20% 30% 40% 50% 60% 70% 80%
Source: Eurostat, Swedbank calculations
What is behind the differences in productivity and how to pro-
ceed?
The most important reason for the different labour productivity levels in Physical and human
Lithuania and other EU countries is the differences in accumulated capi- capital is most important
tal. But only some differences in productivity can be explained by the dif- for productivity.
ferent amounts and quality of capital per employee. To illustrate the main
determinants of productivity, we can employ the Cobb-Douglas produc-
tion function, which represents the relationship between outputs to inputs
as follows2:
y  Ahk  ,
where y is output per employee (labour productivity), A is total factor
productivity (TFP), h is a factor describing the quality of human capital,
k is capital per employee, and  is capital’s share of national income.
Capital per employee in Lithuania varies from 25% to 29% of the ratio in
developed EU countries. It is clear that the natural path towards higher
labour productivity lies along investments in the means of production. Un-
fortunately, gross fixed capital formation contracted dramatically in 2009
and 2010, when it was equal to 17.1% and 16.1% of GDP, respectively,
well below the average of 25% in the first five years after Lithuania’s join-
ing the EU.
Admittedly, most of the investments during the booming years were con-
centrated in residential real estate. Long-term growth in productivity and
output requires investments in tangible fixed assets, machinery, and
2
More on this function and total factor productivity in Europe can be found in e.g.
ECB working paper “Labour Productivity Developments in the Euro Area”.
8 Swedbank Analysis • May 30, 2011

9. equipment, as well as in intangible fixed assets – software and research
and development.
3
Output and capital per employee, TFP, 2010
Lithuania has too little
BE FR IT LT NL FI UK capital--and its quality is
Output per employee,
thousand euro 65 63 50 14 56 65 63 not good.
Capital per employee,
thousand euro 337 316 324 85 299 344 291
Capital per employee in
Lithuania, % of 25% 27% 26% 100% 29% 25% 29%
Capital's share in national
income, % 38% 34% 45% 49% 39% 38% 33%
Total Factor Productivity 7.3 9.0 3.7 1.6 6.2 7.1 9.9
Lithuania TFP, % of 22% 18% 44% 100% 26% 23% 16%
Sources: Eurostat, Swedbank calculations
It is difficult to quantify the quality of human capital available in the econ-
omy, but, as we discussed above, the prospects are bleak. Recent reform
in the higher education system has put Lithuania on the right track, but
the journey is far from complete. Although competition among universities
and colleges has increased the efficiency and quality of services, Lithua-
nia is lagging behind European standards. Some surveys show that more
than half of the students either resort to cheating themselves or do not
condemn such activities. The lack of motivation, creativity, critical think-
ing, and other general skills is inherited from primary and secondary
schools, where the main activity can be described as “memorize and re-
peat.” To foster a creative and entrepreneurial society and to build an
economy dominated by high-value-added services and innovation, one
has to start with appropriate education in the early years.
Finally, TFP describes all the effects on output not caused by inputs. TFP, describing many
Here, differences in TFP are also influenced by differences in the quality qualitative variables in
of human capital, which, as mentioned above, are difficult to quantify. the economy, lags behind
As one can see from the above calculations, the differences in TFP be-
other EU countries
tween Lithuania and other EU countries are even more pronounced than
in labour productivity itself. For example, TFP in Lithuania is six times
smaller than in the UK.
The reasons for these differences in TFP are very broad – TFP depends
(again) on the structure of the economy and manufacturing, the organisa-
tional culture, and the quality and innovativeness of the technologies in
use. TFP also shows how effectively different factors of production (capi-
tal and labour) are combined. Sometimes, countries may have skilled la-
bour but not enough capital for that labour force to work with. This is a
less frequent situation and has an easier solution – skilled labour mi-
grates to non-capital-intensive sectors. To some extent, this is the case in
India and Pakistan, where an educated (usually in the US ) labour force
has enabled high-value-added services sectors to emerge. More often,
like Lithuania today, a country has capital but also low capacity utilisation
3
The quality of human capital is assumed to be fixed and equal to 1. Data on
stock of fixed assets are available only for the year 2005. The amount of capital
available in 2010 was calculated by adding accumulated gross fixed capital for-
mation in the subsequent five years. No capital consumption of fixed capital (de-
preciation) was assumed.
Swedbank Analysis • May 30, 2011 9

10. due to insufficient demand or structural unemployment – as a result, un-
skilled labour cannot be employed.
Most important, TFP—the ability to effectively combine human and physi- The competitive, politi-
cal capital and to create the highest value added--is affected by the eco- cal, judicial, and institu-
nomic, political, judicial, and institutional environment. The complicated tional environments are
tax system and excessive tax burden divert businesses from their optimal important too.
resource and capacity utilisation path towards “tax optimisation” activities.
Distortions in competition, both by different tax exemptions and barriers
to market entry, are too significant a drag on productivity. The institutional
environment, characterised by the time-consuming bureaucratic appara-
tus and a plethora of business-regulating institutions, is another must-fix
area in Lithuania. Finally, the omnipresent corruption and inefficiency of
the judicial system have both direct and indirect effects on business and
its productivity.
Productivity and its determinants are difficult to measure, especially when Reforms must go on.
one has little historical data. Unfortunately, it is very rarely discussed and
analyzed what different new economic policy and regulation measures
would have on productivity and competition. For now, we can only con-
clude that there are many problems in competitive, institutional and judi-
cial environment, but perhaps government could set up a productivity
commission which could observe and analyze productivity (and its obsta-
cles) trends.
The fact, that despite all the aforementioned obstacles and drags, Lithua-
nia was able to enjoy one of the fastest productivity growths in the region,
is encouraging. This, however, does not mean that the reforms and im-
provements can be postponed.
Nerijus Mačiulis
Abbreviations
TFP – Total factor productivity
OECD – Organisation for Economic Co-operation and Development
EU – European Union (27 countries)
EA – Euro area (17 countries)
PISA – Programme for International Student Assessment
PPS – Purchasing power standard
References
Gomez-Salvador, R., Musso, A., Stocker, M. and Turunen, J. (2006). Labour
Productivity Developments in the Euro Area. European Central Bank.
“The service elevator”, The Economist, May 19th 2011.
Programme for International Student Assessment, www.pisa.oecd.org
10 Swedbank Analysis • May 30, 2011

11. Economic Research Department
Sweden
Cecilia Hermansson +46 8 5859 7720 cecilia.hermansson@swedbank.se
Group Chief Economist
Chief Economist, Sweden
Magnus Alvesson +46 8 5859 3341 magnus.alvesson@swedbank.se
Senior Economist
Jörgen Kennemar +46 8 5859 7730 jorgen.kennemar@swedbank.se
Senior Economist
Anna Ibegbulem +46 8 5859 7740 anna.ibegbulem@swedbank.se
Assistant
Estonia
Annika Paabut +372 6 135 440 annika.paabut@swedbank.ee
Acting Chief Economist, Estonia
Elina Allikalt +372 6 131 989 elina.allikalt@swedbank.ee
Senior Economist
Latvia
Mārtiņš Kazāks +371 67 445 859 martins.kazaks@swedbank.lv
Deputy Group Chief Economist
Chief Economist, Latvia
Dainis Stikuts +371 67 445 844 dainis.stikuts@swedbank.lv
Senior Economist
Lija Strašuna +371 67 445 875 lija.strasuna@swedbank.lv
Senior Economist
Lithuania
Nerijus Mačiulis +370 5 258 2237 nerijus.maciulis@swedbank.lt
Chief Economist, Lithuania
Lina Vrubliauskienė +370 5 258 2275 lina.vrubliauskiene@swedbank.lt
Senior Economist
Swedbank Analysis • May 30, 2011 11

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12 Swedbank Analysis • May 30, 2011