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Swedbank Analysis Lithuania, May 30, 2011


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

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Swedbank Analysis Lithuania, May 30, 2011

  1. 1. Swedbank Analysis May 30, 2011Lithuania’s productivity is gaining, but pacecould 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 rapidlyLabour productivity measures the amount of goods and services pro-duced per each member of the labour force or per hour worked. It is oneof a country’s most important indicators of economic progress. However,it is influenced by many different, and sometimes nonmeasurable, factorsthat 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 growthit was 60 percent higher than in 2000 and twice as large as in 1995. In was among the fastest incontrast, 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: Legally responsible publisher: Cecilia Hermansson, +46-8-5859 7720 Nerijus Mačiulis + 370 5 258 2237. Lina Vrubliauskienė +370 5 258 2275
  2. 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: EurostatIn 2009, labour productivity contracted by 8.5%, but most of the losseswere regained in 2010. The loss in productivity was caused by plummet-ing demand and a contraction in output. The recovery however happeneddue 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 causedby investments and improvement in human capital. However, this yearand 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 laboureuro area average. productivity is still less than one- fourth of theReal 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: EurostatAlthough over the past 10 years real labour productivity per hour workedhas improved significantly in all three Baltic countries, there is still a lot ofcatching up to do. Lithuania’s labour productivity is at 23% of the euroarea average, above Latvia’s (20%), but below Estonia’s (27%).The difference is less striking when one compares labour productivity atthe purchasing power standard (PPS) – all three Baltic countries haveexceeded the EU average. Estonia’s productivity, at 65.5%, is closest tothe EU average, followed by Lithuania’s, at 57.3%, and Latvia’s, at53.0%.2 Swedbank Analysis • May 30, 2011
  3. 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 calculationsNormally, 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 reflectLithuanian employees is only 51.1% of the EU average, i.e., convergencein wages is lagging behind productivity. This is not the case for Estonia, productivity.where compensation of employees is closer to the EU average than isproductivity. Naturally, this is not an ideal benchmark, since compensa-tion of employees also differs across sectors. Furthermore, even withinthe same sectors differences in capital intensity and innovation play arole.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 calculationsIn general, besides investments in fixed tangible assets and improve-ments in human capital, the changing structure of the economy explainsmost of the productivity gains.Less agriculture, more manufacturing and servicesLabour 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 movingthe classical textbook path of an agricultural economy becoming indus- up the value-addedtrial 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 thepast decade were replaced by smaller and more dynamic manufacturingbranches.Swedbank Analysis • May 30, 2011 3
  4. 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 hasbeen 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, EurostatThe 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 EUaverage.Hotels and restaurants, as well as financial intermediation, create, re-spectively, 1.2% and 2.4% of value added in the economy. This sharehas 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, comparedwith an average of 74% in the EU. This is one reason why productivitywas converging faster – most services are usually considered as havinga low-growth productivity (there are a very limited number of haircuts youcan 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 ascatering or making haircuts). In the aforementioned countries, unlike inLithuania, the level of productivity is higher in services than in industry.Should Lithuania continue relying on manufacturing or focus on modern Services sectors provideservices? A recently drafted long-term strategy (“Lithuania 2030”) implies possibilities…the latter option should be taken. The current government has been veryactive in attracting big international companies (Barclays, IBM, WesternUnion, e.g.), all of which have invested in high-value-added services.Lithuania is leading in many quantitative education indicators. In 2009, forexample, of the population aged 20-29, 87.8 out of 1,000 were universitygraduates; this compares favourably with the average of around 60 in theEU. The ratio of students to teacher is the lowest is Europe, two timessmaller than in Germany (indicating that more attention can be paid to1 See, e.g. Swedbank Analysis • May 30, 2011
  5. 5. each student). However, some of these high quantitative indicators sug-gest that the education sector (dominated by public institutions) has notbeen able to adjust and adapt to the dwindling population.Good quantitative indicators are not reflected in an equally good outcome …but demand for skilledof tertiary education. The latest results from the Programme for Interna- labour faces challengestional Student Assessment (PISA), coordinated by the OECD, show that due to the poor quality ofLithuania is “statistically significantly below the OECD average.” On the higher education.overall scale, Lithuania was ranked 40th, Latvia 30th, and Estonia 13th. Onthe overall reading scale (considering the ability to access and retrieve,integrate and interpret, and reflect and evaluate) Lithuania scored 468points, below the OECD average of 493. On the mathematics and sci-ence scale, Lithuanian students scored 477 and 491 points, below theaverages 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, PISAThe recent higher education reform, which encourages competitionamong universities, points in the right direction and over time will improvethe quality of education. Some of the problems (low motivation, lack ofcritical 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 sectorsProductivity changes within different sectors were far from universal. Not all sectors improvedOver the last decade, the biggest productivity gains were recorded in their productivity in theelectricity, gas, and water supply, agriculture, and manufacturing. In this past decade.period, many companies in the electricity, gas and water supply sectorwere 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 wasvery unproductive to start with, and thus some of its rapid improvement isexplained 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 tosignificantly boost the productivity. Many small farms merged into biggerconglomerates, allowing benefiting from economies of scale.Swedbank Analysis • May 30, 2011 5
  6. 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: EurostatManufacturing and transport, storage, and communication services were EU support and FDIthe two sectors that attracted most foreign direct investments in the pre- were important factorsvious decade; thus, their productivity improvement was also stellar. behind productivityAlthough productivity in the financial intermediation sector in 2010 was growth.below its 2000 level, this was mainly because of the grave effects of thefinancial crisis – labour productivity declined by 30% from the peakreached in 2007. Another reason why this sector in Lithuania still has afairly 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 – likeutilities 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 calculationOverall in the economy, value added per employee is equal to 27% of theeuro area average, ranging from 22% in the public sector and 37% in thewholesale and retail trade, hotels and restaurants, and transport sector.6 Swedbank Analysis • May 30, 2011
  7. 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, SwedbankDifferent branches of manufacturing have converged towards the euroarea average very unevenly. The biggest productivity increases were inthe highest-value-added manufacturing branches - machinery andequipment, 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 inthe 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 moreDeclining demand was followed by dropping productivity, because em- than employment.ployment contracted slower than demand. Overall, gross value added inmanufacturing contracted by 15% in 2009, whereas employment droppedby 12.3%.Manufacturers of electrical and optical equipment were among the fewmanaging to increased productivity in both 2008 and 2009, not only bothbecause their output dropped by “only” 16%, but also because this sectorshed 22.4% of its jobs. In 2009, production of rubber and plasticsdropped by 20.6%, but employment increased by 28.2%, thus accountingfor the sharp drop in productivity. In retrospect, this jump in employmentwas not too reckless, as demand for these products picked up veryquickly 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 calculationsSwedbank Analysis • May 30, 2011 7
  8. 8. Currently, productivity in manufacturing of refined petroleum products, at Not all manufacturers70%, is closest to the EA average. But this comes from just one com- managed to improvepany, previously owned by US capital and now owned by one of the big- productivity faster thangest refinery in Central and Eastern Euope– PKN Orlen. Productivity in the EA average.manufacturing of electrical and optical equipment (45%) and transportequipment (39%) has also converged towards the EA average. However,producers of nonmetallic mineral products, leather, and chemicals are stillgenerating 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 calculationsWhat is behind the differences in productivity and how to pro-ceed?The most important reason for the different labour productivity levels in Physical and humanLithuania and other EU countries is the differences in accumulated capi- capital is most importanttal. 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 maindeterminants of productivity, we can employ the Cobb-Douglas produc-tion function, which represents the relationship between outputs to inputsas follows2: y  Ahk  ,where y is output per employee (labour productivity), A is total factorproductivity (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 indeveloped EU countries. It is clear that the natural path towards higherlabour productivity lies along investments in the means of production. Un-fortunately, gross fixed capital formation contracted dramatically in 2009and 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 andoutput requires investments in tangible fixed assets, machinery, and2 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. 9. equipment, as well as in intangible fixed assets – software and researchand development. 3Output 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% Capitals 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 calculationsIt is difficult to quantify the quality of human capital available in the econ-omy, but, as we discussed above, the prospects are bleak. Recent reformin the higher education system has put Lithuania on the right track, butthe journey is far from complete. Although competition among universitiesand colleges has increased the efficiency and quality of services, Lithua-nia is lagging behind European standards. Some surveys show that morethan half of the students either resort to cheating themselves or do notcondemn such activities. The lack of motivation, creativity, critical think-ing, and other general skills is inherited from primary and secondaryschools, where the main activity can be described as “memorize and re-peat.” To foster a creative and entrepreneurial society and to build aneconomy dominated by high-value-added services and innovation, onehas to start with appropriate education in the early years.Finally, TFP describes all the effects on output not caused by inputs. TFP, describing manyHere, differences in TFP are also influenced by differences in the quality qualitative variables inof human capital, which, as mentioned above, are difficult to quantify. the economy, lags behindAs one can see from the above calculations, the differences in TFP be- other EU countriestween Lithuania and other EU countries are even more pronounced thanin labour productivity itself. For example, TFP in Lithuania is six timessmaller 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 inuse. 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 aless frequent situation and has an easier solution – skilled labour mi-grates to non-capital-intensive sectors. To some extent, this is the case inIndia and Pakistan, where an educated (usually in the US ) labour forcehas enabled high-value-added services sectors to emerge. More often,like Lithuania today, a country has capital but also low capacity utilisation3 The quality of human capital is assumed to be fixed and equal to 1. Data onstock of fixed assets are available only for the year 2005. The amount of capitalavailable 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. 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 aretax 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 barriersto market entry, are too significant a drag on productivity. The institutionalenvironment, characterised by the time-consuming bureaucratic appara-tus and a plethora of business-regulating institutions, is another must-fixarea in Lithuania. Finally, the omnipresent corruption and inefficiency ofthe judicial system have both direct and indirect effects on business andits productivity.Productivity and its determinants are difficult to measure, especially when Reforms must go has little historical data. Unfortunately, it is very rarely discussed andanalyzed what different new economic policy and regulation measureswould 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 productivitycommission 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 MačiulisAbbreviationsTFP – Total factor productivityOECD – Organisation for Economic Co-operation and DevelopmentEU – European Union (27 countries)EA – Euro area (17 countries)PISA – Programme for International Student AssessmentPPS – Purchasing power standardReferencesGomez-Salvador, R., Musso, A., Stocker, M. and Turunen, J. (2006). LabourProductivity Developments in the Euro Area. European Central Bank.“The service elevator”, The Economist, May 19th 2011.Programme for International Student Assessment, www.pisa.oecd.org10 Swedbank Analysis • May 30, 2011
  11. 11. Economic Research DepartmentSwedenCecilia Hermansson +46 8 5859 7720 cecilia.hermansson@swedbank.seGroup Chief EconomistChief Economist, SwedenMagnus Alvesson +46 8 5859 3341 magnus.alvesson@swedbank.seSenior EconomistJörgen Kennemar +46 8 5859 7730 jorgen.kennemar@swedbank.seSenior EconomistAnna Ibegbulem +46 8 5859 7740 anna.ibegbulem@swedbank.seAssistantEstoniaAnnika Paabut +372 6 135 440 annika.paabut@swedbank.eeActing Chief Economist, EstoniaElina Allikalt +372 6 131 989 elina.allikalt@swedbank.eeSenior EconomistLatviaMārtiņš Kazāks +371 67 445 859 martins.kazaks@swedbank.lvDeputy Group Chief EconomistChief Economist, LatviaDainis Stikuts +371 67 445 844 dainis.stikuts@swedbank.lvSenior EconomistLija Strašuna +371 67 445 875 lija.strasuna@swedbank.lvSenior EconomistLithuaniaNerijus Mačiulis +370 5 258 2237 nerijus.maciulis@swedbank.ltChief Economist, LithuaniaLina Vrubliauskienė +370 5 258 2275 lina.vrubliauskiene@swedbank.ltSenior EconomistSwedbank Analysis • May 30, 2011 11
  12. 12. DisclaimerThis research report has been prepared by economists of Swedbank’s Economic Research Depart-ment. The Economic Research Department consists of research units in Estonia, Latvia, Lithuania,and Sweden, is independent of other departments of Swedbank AB (publ) (“Swedbank”) and respon-sible for preparing reports on global and home market economic developments. The activities of thisresearch department differ from the activities of other departments of Swedbank, and therefore theopinions expressed in the reports are independent from interests and opinions that might be expressedby other employees of Swedbank.This report is based on information available to the public, which is deemed to be reliable, and re-flects the economists’ personal and professional opinions of such information. It reflects the econo-mists’ best understanding of the information at the moment the research was prepared and due tochange of circumstances such understanding might change accordingly.This report has been prepared pursuant to the best skills of the economists and with respect to theirbest knowledge this report is correct and accurate, however neither Swedbank nor any enterprise be-longing to Swedbank or Swedbank directors, officers, or other employees or affiliates shall be liablefor any loss or damage, direct or indirect, based on any flaws or faults within this report.Enterprises belonging to Swedbank might have holdings in the enterprises mentioned in this reportand provide financial services (issue loans, among others) to them. Aforementioned circumstancesmight influence the economic activities of such companies and the prices of securities issued by them.The research presented to you is of an informative nature. This report should in no way be interpretedas a promise or confirmation of Swedbank or any of its directors, officers, or employees that theevents described in the report shall take place or that the forecasts turn out to be accurate. This reportis not a recommendation to invest into securities or in any other way enter into any financial transac-tions based on the report. Swedbank and its directors, officers, or employees shall not be liable forany loss that you may suffer as a result of relying on this report.We stress that forecasting the developments of the economic environment is somewhat speculative innature, and the real situation might turn out different from what this report presumes.IF YOU DECIDE TO OPERATE ON THE BASIS OF THIS REPORT, THEN YOU ACT SOLELY ONYOUR OWN RISK AND ARE OBLIGED TO VERIFY AND ESTIMATE THE ECONOMIC REASON-ABILITY AND THE RISKS OF SUCH ACTION INDEPENDENTLY.12 Swedbank Analysis • May 30, 2011