LITHUANIAN ECONOMIC
REVIEW
2016
2016
JUNE
ISSN 2029-8471 (online)
Lithuanian Economic Review analyses the developments of the real sector, prices,
public finance and credit in Lithuania, as well as the projected development of the domestic
economy. The material presented in the Review is the result of statistical data analysis,
modelling and expert assessment. The Review is prepared by the Bank of Lithuania.
During the preparation of the Lithuanian Economic Review, the data of the Bank of Lithuania, Statistics Lithuania,
the European Central Bank, Eurostat, the International Monetary Fund and other data published up to 17 May 2016
were used.
Reprinting is allowed only for education and non-commercial purposes, if the source is indicated.
© Lietuvos bankas, 2016
Contents
LITHUANIA’S ECONOMIC DEVELOPMENT AND OUTLOOK ................................................................................................................ 3
I. INTERNATIONAL ENVIRONMENT ...................................................................................................................................................... 5
II. MONETARY POLICY OF THE EUROSYSTEM ................................................................................................................................... 8
III. REAL SECTOR ................................................................................................................................................................................ 11
IV. LABOUR MARKET........................................................................................................................................................................... 13
V. EXTERNAL SECTOR ....................................................................................................................................................................... 14
VI. PRICES AND COSTS ...................................................................................................................................................................... 16
VII. FINANCING OF THE ECONOMY ................................................................................................................................................... 18
VIII. GENERAL GOVERNMENT FINANCES ......................................................................................................................................... 20
ANNEXES ............................................................................................................................................................................................. 22
ANNEX 1. Non-standard monetary policy measures of the ECB ...................................................................................................... 22
ANNEX 2. Differences in average compensation for employees across the Baltic States ................................................................. 27
ANNEX 3. Impact of labour market reforms on Lithuania’s economy ................................................................................................ 31
2
Table
GDP developments and inflation in selected advanced and emerging market economies……..……………………………….………...……………………..…….5
Charts
Chart 1. Development of Purchasing Managers’ Indices ............................................................................................................................................................... 5
Chart 2. Unemployment rate in the US and the euro area ............................................................................................................................................................ 5
Chart 3. General government debt-to-GDP ratio ........................................................................................................................................................................... 6
Chart 4. Real GDP changes in Lithuania’s export partners ........................................................................................................................................................... 6
Chart 5. ECB interest rates and 6-month EURIBOR ..................................................................................................................................................................... 8
Chart 6. Key ECB interest rates and inflation................................................................................................................................................................................. 8
Chart 7. Annual yields on euro area government bonds with a maturity close to 10 years, issued in national currencies .......................................................... 8
Chart 8. Average interest rates on new MFI housing loans .......................................................................................................................................................... 9
Chart 9. Average interest rate on new MFI loans to non-financial corporations .......................................................................................................................... 9
Chart 10. Dynamics of MFI loans to households and non-financial corporations in the euro area and Lithuania ........................................................................ 9
Chart 11. Real effective exchange rate of the euro and Lithuanian currency (the litas until 2015 and the euro afterwards) ..................................................... 10
Chart 12. Contributions to real GDP by expenditure approach ................................................................................................................................................... 11
Chart 13. External demand and real exports of goods and services (at constant prices, seasonally adjusted) ......................................................................... 11
Chart 14. Contributions to changes in households’ disposable income (at constant prices) ...................................................................................................... 11
Chart 15. Contributions to investment changes (at constant prices) ........................................................................................................................................... 12
Chart 16. Contributions to labour force dynamics ........................................................................................................................................................................ 13
Chart 17. Contributions to job dynamics ..................................................................................................................................................................................... 13
Chart 18. Wage dynamics ............................................................................................................................................................................................................ 13
Chart 19. Lithuania’s exports, excluding mineral products, as broken down by country groups ................................................................................................ 14
Chart 20. Dynamics of the oil refining margin of AB ORLEN Lietuva .......................................................................................................................................... 14
Chart 21. Components of the current account balance ............................................................................................................................................................... 14
Chart 22. Contributions to annual HICP inflation ......................................................................................................................................................................... 16
Chart 23. Price dynamics of industrial goods and market services ............................................................................................................................................. 16
Chart 24. Food price dynamics .................................................................................................................................................................................................... 16
Chart 25. Contributions to changes in the portfolio of MFI loans to the private sector ................................................................................................................ 18
Chart 26. Interest rates ................................................................................................................................................................................................................. 18
Chart 27. Loans by economic activity........................................................................................................................................................................................... 18
Chart 28. General government revenue, expenditure and balance when adjusted for one-off factors (4-quarter moving sum) ................................................ 20
Chart 29. Contributions to the general government revenue-to-GDP ratio (taxes and social contributions, 4-quarter moving sum) ......................................... 20
Chart 30. Contributions to general government revenue ............................................................................................................................................................. 20
Chart 31. Contributions to general government expenditure ....................................................................................................................................................... 21
Chart 32. Contributions to the general government debt-to-GDP ratio ....................................................................................................................................... 21
LITHUANIAN ECONOMIC REVIEW / June 2016
Abbreviations
AB
ABSPP
ALMPs
APP
CBPP
CIS
EC
ECB
EONIA
EU
EURIBOR
Eurostat
FED
GDP
HICP
IMF
ITR
LTRO
MFI
MRO
OECD
OMT
PPP
SMP
TLTRO
UK
US
VAT
VĮ
public company
asset-backed securities purchase programme
active labour market policies
asset purchase programme
covered bond purchase programme
Commonwealth of Independent States
European Commission
European Central Bank
euro overnight index average
European Union
Euro Interbank Offered Rate
statistical office of the European Union
Federal Reserve
gross domestic product
Harmonised Index of Consumer Prices
International Monetary Fund
implicite tax rate
longer-term refinancing operation
monetary financial institution
main refinancing operation
Organisation for Economic Co-operation and Development
Outright Monetary Transactions
purchasing power parity
Securities Market Programme
targeted longer-term refinancing operation
United Kingdom
United States of America
value-added tax
state enterprise
Lithuania’s Economic Development and Outlook
3
Global economic development continues to be uneven, but the economies of Lithuania’s major trading partners are on the rise or their economic activity is not declining to the extent it did last year. The euro area economy
continues to recover: after beginning to recover in 2013, it has currently achieved such a level that annual GDP growth,
driven by private consumption and investment, has been above 1.5 per cent for four consecutive quarters. Economic
growth entails the improvement of labour market indicators, growth in household income, increase in demand for goods
and services from other countries and, thus, from Lithuania. This boosts Lithuanian exports. Increasingly more goods are
exported to euro area and other EU countries, the exports of services increase as well. The freight activity, carried out by
Lithuanian enterprises, has contracted significantly, when Russia imposed trade restrictions and its economy began to fall;
however, at the end of 2015, Lithuania’s transportation sector posted growth again. Major contribution to the improvement
of this sector’s economic activity stemmed not from carrying freights into/from Lithuania, but carrying them from country to
country. After a previously substantial contribution to the deceleration of economic growth in Lithuania, the transportation
sector currently contributes markedly to its recovery.
The East-oriented export situation is relatively stable. After contracting significantly in 2015, the value of exports to
Russia currently remains basically unchanged. The economic situation in Russia is less volatile as well. After dropping by
3.7 per cent last year, Russia’s real GDP fell by 1.2 per cent year on year in the first quarter of 2016. Domestic demand in
Russia continues to decrease, though not as strongly as before; consequently, the fall in Russian imports is not as marked
as last year. The share of the exports of goods to Russia in total exports of Lithuania has contracted substantially. Previously it used to account for a fifth of the country’s total exports, while now it only accounts for slightly more than 12 per
cent. Nevertheless, even this share is not small; hence, the absence of recovery in exports to Russia has been affecting
Lithuania’s overall export performance.
Economic growth in Lithuania is driven to a large extent by domestic demand. The employment and unemployment indicators have been improving for approximately five years already. Lower exports to Russia have only marginally
affected the labour market; only two economic activities — trade and transportation — have been affected somewhat
negatively. However, the employment rate within these sectors did not decrease; it only increased weaker than in previous
periods. The deteriorating construction sector situation contributes negatively to demand for employees within this sector,
affecting overall employment in the country relatively marginally as well. The employment rate within other economic
activities increases further quite strongly. Survey data suggests that an increasingly larger share of enterprises, except for
those engaged in the construction activity, have been facing the staff insufficiency issue. The job vacancy rate has been
rising gradually. This has an obvious effect on wage dynamics. Wages used to rise by approximately 5 per cent in recent
years, while this year, with unemployment declining further and minimum wage rising, its growth rate is likely to accelerate
even more. Such labour income dynamics affects private consumption and it continues to increase amid moderate price
level growth. In addition, low interest rates on loans provide the conditions for this growth. With low interest rates, the
payment burden of households with loans becomes easier and the amount of new loans being granted increases.
Domestic demand will remain an important factor behind economic expansion during the projection horizon of
2016–2017. The labour market situation suggests that labour income is likely to increase further, which will encourage
consumption. Investment dynamics is likely to change though: after the possibility to use the funds of the previous EU
financial perspective ends, investment growth is not likely to be as strong as before.
Unlike last year, exports will contribute to economic growth as well. A more favourable international environment
is likely to improve export performance and accelerate the development of the domestic economy. Lithuania’s real GDP is
projected to increase by 2.6 per cent in 2016 — markedly more than in 2015 (1.6%). In the following period (i.e. in 2017),
economic development is likely to accelerate even more due to the transmission of future improvement in the economic
development in a number of regions across the world.
Inflation is still low and is expected to get close to a 2 per cent rate in 2017. The prices of some groups of goods
and services have been rising, but the aggregate price level has been increasing marginally: the consumer price indicator
for the initial four months of this year is 0.7 per cent above the level of the previous year. Similar to last year, the increase
in the prices of services is more pronounced, reflecting markedly increasing domestic demand and labour costs. The
increase in the latter is driven by strong wage increases in the services sector. Wages have been outpacing labour productivity longer than in other sectors — for four years already. Food prices are also on the rise this year; however, prices that
are anyway characterised by permanent fluctuation — of vegetables and fruit — have been posting the highest increases.
LITHUANIAN ECONOMIC REVIEW / June 2016
Investment grew until the end of 2015 as well, driven not only by the low interest rate environment but also more active
use of EU support funds. As the time for using funds from the 2007–2013 EU financial perspective was running out, last
year the use of funds intensified. Investment continued to be underpinned by the need to expand production capacity. The
level of the use of manufacturing capacity has been above its long-term average for four years already. It should be noted,
however, that recently investment in machinery and equipment grew the most, while investment in buildings and constructions decelerated. This had a downward effect on construction activity, which previously had contributed significantly to
economic development. Out of all types of construction activities, only residential construction contributed positively to
economic activity of construction.
4
The increases in other food prices are relatively marginal. The aggregate price level is still being reduced by prices
related to global energy commodity markets: fuel and administered prices, notably heat energy prices, continue to be
lower than a year ago. However, oil prices are now higher than in previous macroeconomic projections. This is one of
the major reasons for the projected higher inflation rate in 2016. According to current projections, inflation will be 0.9 per
cent in 2016 (previous projection — 0.5%) and 1.9 per cent in 2017 (previous projection — 1.8%).
Outlook for Lithuania’s economy in 2016–2017
June 2016 projectiona
March 2016 projection
2015
2016b
2017b
2015b
2016b
2017b
–0.7
0.9
1.9
–0.7
0.5
1.8
0.3
0.9
2.0
0.1
0.8
2.0
Price and cost developments (annual percentage changes)
Average annual inflation, as measured by the HICP
GDP
deflatorc
Wages
5.1
5.7
5.5
5.1
5.3
5.3
Import deflatorc
–6.9
–4.0
1.5
–6.4
–3.1
1.4
Export deflatorc
–3.9
–3.2
1.4
–3.8
–2.7
1.4
Economic activity (constant prices; annual percentage changes)
Gross domestic productc
1.6
2.6
3.3
1.7
2.6
3.4
Private consumption
expenditurec
4.8
4.3
3.9
4.9
4.2
4.0
General government consumption expenditurec
1.9
1.2
1.2
2.1
0.9
1.2
Gross fixed capital formationc
10.9
1.3
7.2
9.6
2.4
7.4
Exports of goods and
servicesc
–0.1
2.9
4.2
1.0
2.9
4.8
Imports of goods and
servicesc
6.0
2.9
5.2
6.9
3.2
5.7
9.1
8.3
7.9
9.1
8.6
8.3
1.3
0.7
0.0
1.2
0.2
0.1
Balance of goods and services
–0.2
0.4
–0.3
–0.5
–0.5
–1.2
Current account balance
–1.7
–0.1
–0.6
–2.1
–1.9
–2.7
Current and capital account balance
1.3
1.9
1.8
0.9
0.2
–0.1
Labour market
Unemployment rate (annual average as a percentage of labour
force)
Employmentd (annual percentage changes)
External sector (as a percentage of GDP)
projections of macroeconomic indicators are based on information made available by 17 May 2016
b Projection
c Adjusted for seasonal and workday effects
d National accounts data; employment in domestic concept
LITHUANIAN ECONOMIC REVIEW / June 2016
a These
I. INTERNATIONAL ENVIRONMENT
After the slowdown in 2015, global economic growth is expected to accelerate slightly; however, a number of factors pose
the risk of economic growth to be lower than expected. According
to the IMF estimates, global real GDP picked up by 3.1 per cent in
2015, a decrease of 0.3 p.p. compared to 2014, while only a slight
acceleration (up to 3.2%) is projected for this year. The development
of the global economy will be contained not only by continued difficulties in some emerging markets, but also by the still weak growth
momentum in advanced economies. China’s real GDP development is
projeced to slow down to 6.5 per cent in 2016. The state of its economy is monitored very closely due to its size and intensive trade links
with other countries. Chinese economic data has a profound impact
on the economic development of its trade partners and prices of
various commodities, and determines fluctuations in global financial
markets. With no expectations for oil prices to recover, Russia is
expected to remain in recession; however, the decline in its economic
activity is expected to be less pronounced. No improvement of the
economic situation is expected in other export-oriented commodity
markets, which have to look for new sources to support their economic
growth. No acceleration of economic growth is anticipated in advanced economies either. Economic growth in some of them will
stumble due to the aftermath of the financial crisis, such as a high
debt level or weak investment growth (for example, in the euro area),
whereas in other countries, economic growth will be stunted due to the
adverse dynamics of net exports (as in the US and Japan). Confidence indicators and survey results also confirm that no stronger
increase in economic activity can be expected in the near future. For
instance, Purchasing Managers’ Indices, which are linked with GDP
growth to some extent, fell in the first quarter of 2016. Other indicators
— the Economic Sentiment Indicator published by the European
Commission, composite leading indicators as calculated by OECD —
point to the same trends as well. High volatility of financial markets,
fluctuations in commodity prices, as well as previous and new macroeconomic imbalances pose the risk of potentially weaker global
economic developments than currently forecasted.
5
According to the IMF estimates, the growth pace of the
global economy will increase in 2016, advanced
economies will grow at the same pace as in 2015, while
the growth pace of emerging market economies will be
slightly higher.
GDP developments and inflation in selected advanced and
emerging market economies
2015
2016*
2017*
Global
3.1
3.2
3.5
Advanced economies
1.9
1.9
2.0
2.4
2.4
2.5
1.6
1.5
1.6
4.0
4.1
4.6
6.9
6.5
6.2
–3.7
–1.8
0.8
0.3
0.7
1.5
0.1
0.0
0.8
0.4
1.5
1.1
4.7
4.5
4.2
1.4
15.5
1.8
8.4
2.0
6.5
Real GDP change, per cent
USA
Euro area
Emerging market economies
China
Russia
Inflation, percentage
Advanced economies
USA
Euro area
Emerging market economies
China
Russia
Source: IMF.
* Forecasts.
Expectations regarding the growth prospects for the
global economy have been cautious. This can be seen
from global Purchasing Manager’s Indices that have
been decreasing since the second half of 2015.
Chart 1. Development of Purchasing Managers’ Indices
Index
57
56
55
54
53
52
51
The growth of the US economy slowed down in the last quarter of 2015 and the beginning of 2016. Lower oil prices determined
a decrease in investment in the energy sector, the appreciation of the
US dollar had a negative effect on the development of exports and
manufacturing; consumer expectations decreased at the beginning of
50
49
48
2012
2013
2014
2015
2016
Global Composite PMI
Global Manufacturing PMI
Global Services PMI
Source: Markit.
The unemployment rate continues to decrease gradually both in the US and the euro area, but regional
differences remain high. At the beginning of 2016, the
unemployment level in the US was 5 per cent, while in
the euro area it still hovered above 10 per cent.
Chart 2. Unemployment rate in the US and the euro area
13
Per cent
12
11
10
9
8
7
6
5
4
2012
2013
2014
Unemployment in the US
Unemployment in the euro area
Sources: Eurostat and U.S. Bureau of Labor Statistics.
Sources: Eurostat, US Labor Force Statistics Bureau.
2015
2016
LITHUANIAN ECONOMIC REVIEW / June 2016
With inflation and its expectations remaining low and uncertainty over global economic growth prospects increasing, major
central banks continued to ease their monetary policy stance at
the beginning of 2016. In January, the central bank of Japan adopted
negative interest rates (–0.1% on some deposits with banks). In
February, Sweden’s central bank (Sveriges Riksbank) cut its main
repo rate down to –0.5 per cent and expanded the volume of its
government bond purchase programme in April. In March, the Eurosystem also reinforced its accommodative monetary policy stance.
With inflation in the US staying below the target rate (2% over the
medium term) and mounting fears over the further prospects of
economic developments, expectations that key interest rates applied
by the Federal Reserve System may remain low longer than previously expected (at the moment, they amount to 0.25 to 0.5%) have
increased. In recent years, the Bank of England has changed neither
the interest rate (0.5%), nor the total volume of its quantitative easing
programme (GBP 375 billion), while market expectations regarding the
tightening of the monetary policy have been pushed back as well.
6
The general government debt-to-GDP ratio remains high
in major euro area countries. Since 2012, it has been
gradually decreasing only in Germany.
Chart 3. General government debt-to-GDP ratio
Per cent
144
134
124
114
104
94
84
74
64
2012
2013
2014
2015
Germany
Spain
France
Italy
Source: Eurostat.
According to the forecasts for 2016, Russia will remain
in recession and Latvia’s real GDP will grow at a slower
pace, but the economic situation in Lithuania’s other
export partners will improve or be similar to that in
2015.
Chart 4. Real GDP changes in Lithuania’s export partners
Per cent, annual change
7
5
3
1
–1
–3
–5
2012
2013
2014
2015
Germany
Latvia
Poland
Estonia
Russia
LITHUANIAN ECONOMIC REVIEW / June 2016
Sources: Eurostat and Russian Federation Federal State Statistics Service.
2016
the year, while the results of retail trade were worse than expected.
However, other economic indicators exceeded expectations. For
example, the labour market situation remained good: unemployment
still fluctuated at around 5 per cent and was one of the lowest in the
group of advanced economies, while employment has been growing
moderately over the past years. According to the IMF estimates, the
growth of the US economy should stay at around 2.4 per cent, similar
to that in 2015.
According to the estimates of various institutions, the euro
area economy is likely to grow by approximately 1.5 to 1.6 per
cent this year, hence no growth acceleration is expected. Euro
area real GDP growth remained stable over the past few quarters, at
around 1.5 to 1.6 per cent per year. Although short-term economic
data suggests that the region’s economy will continue to grow at a
similar pace (stable growth is observed in retail sales income, the low
interest rate environment has a positive effect on the domestic demand, commodity prices have decreased), some signs of a slowdown
in economic activity can be observed. Results of business and consumer surveys worsened at the beginning of the year and changes in
the external environment were unfavourable (deceleration of economic growth in China, recession in Russia, weaker growth in the US);
moreover, the growth of the euro area economy continued to be
dampened by a huge debt of the private and public sectors in some
countries, high unemployment rate, and modest investment growth.
Factors that have existed for some time as well as new ones
are posing risks to growth prospects for the euro area economy.
At the beginning of the year, the risks, such as the economic slowdown in China, the complicated financial and economic situation in
Greece, or the migration crisis, which have been observed for some
time, were accompanied by mounting fears over the banking sector’s
stability and the EU membership referendum scheduled to take place
in the United Kingdom. With a nearly equal proportion of supporters
and opponents of the UK staying in the EU, the result of the referendum planned for 23 June is difficult to predict, and such uncertainty
has already been affecting the country’s economic indicators. For
example, the British pound sterling depreciated, confidence indicators
worsened, and UK’s GDP growth forecast was downgraded in the first
half of the year. Various institutions (such as the Bank of England,
OECD, IMF, etc.) have issued warnings that the UK’s decision to
leave the EU would have a negative impact on the national economy
in the long-term. Though the impact assesments (regarding the
assumptions about the openess of the economy, changed trading
terms, currency exchange rate, etc.) are mixed, it is commonly agreed
that increased uncertainty would boost volatility in the regional financial markets, affect consumption and investment decisions of households, property prices, while currency depreciation would exert
inflationary pressure.
In the first half of the year, tensions in EU financial markets also
grew due to the failure to reach an agreement on the first review of
Greece’s macroeconomic adjustment programme. Amid disagreement
between institutions over structural reforms, debt relief, the IMF’s
participation and other issues, no agreement was reached by the end
of May. After completing the review, a portion of the loan would be
transferred to Greece to ensure its ability to pay the creditors in July
this year. Moreover, the immigration crisis has continued to raise
tensions in the region. While the flow of refugees has subsided
gradually after the deal with Turkey, there is disagreement on the
further granting of asylum to immigrants, their integration and control
of inner borders; moreover, immigrant flows may surge again, which
would continue posing political instability risks and boosting uncertainty across the region.
The economic situation and economic development trends in
major Lithuania’s export partners are mixed. In 2015, Russia’s
real GDP shrank by 3.7 per cent. According to IMF forecasts, the
downturn should decrease this year to around 1.8 per cent, while in
2017 a slight growth of up to 0.8 per cent is expected. However,
further growth prospects will depend on commodity price developments and the duration of the application of economic sanctions.
According to current forecasts, average oil price in 2016 will be lower
than in 2015, yet it will grow somewhat in 2017; however, so far the
EU sanctions for Russia have been extended untill the summer of
2016. Lower disposable income and residents’ purchasing power will
continue having a negative impact on household consumption in
Russia, while limited borrowing possibilities lead to a decrease in
investment.
7
LITHUANIAN ECONOMIC REVIEW / June 2016
In 2016, a slight recovery in investment and export is expected in
Estonia, which should prompt acceleration of the country’s real GDP
growth. Economic growth in Latvia may decelerate as it will be limited
by the construction and transportation economic actvities and lower
contribution from manufacturing. In Poland, economic growth is further
driven by domestic demand, which is expected to strengthen due to
increasing social benefits. Economic growth in Poland in 2016 is
projected to be among the highest in the EU, at around 3.6 to
3.7 per cent. Regarding Germany’s economy, adverse dynamics of
external demand should be offset by strengthening domestic demand,
as the growth of household consumption and general government
expenditure is expected to accelerate.
II. MONETARY POLICY OF THE EUROSYSTEM
8
ECB interest rates and EURIBOR are the lowest since
the beginning of the euro area.
Chart 5. ECB interest rates and 6-month EURIBOR
Per cent
6
5
4
3
The Eurosystem further reinforced the accommodative monetary
policy stance. At the end of 2015 and in the first quarter of 2016, the
Eurosystem continued implementing accommodative monetary policy
measures seeking to prevent disinflationary trends, adjust expectations, as
well as maintain sustained economic growth in the euro area countries. It
continued cutting ECB interest rates, enlarging the extended APP
launched in March 2015, and announced about a new series of the targeted longer-term refinancing operations (TLTROs).
2
1
0
–1
1999
2001 2003 2005 2007
Interest rate on MRO
Deposit facility
Marginal lending facility
6-month EURIBOR
2009
2011
2013
2015
Source: Thomson Reuters.
In response to sluggish euro area economic recovery
and falling inflation, the Eurosystem has been gradually
cutting ECB interest rates since 2011.
Chart 6. Key ECB interest rates and inflation
Per cent
6
5
4
3
2
1
0
–1
1999
2001
2003
2005
2007
2009
2011
2013
2015
Interest rate on MRO
Deposit facility
Annual HICP development
Source: Thomson Reuters.
Yields on bonds purchased under the expanded asset
purchase programme declined mainly due to the
strengthening of market expectations regarding the
future announcement of the programme. Later, yields
also changed because of adjustments in economic
forecasts for the euro area.
Chart 7. Annual yields on euro area government bonds with
a maturity close to 10 years, issued in national currencies
Per cent
The Eurosystem cut ECB interest rates to new record lows. The
Governing Council of the ECB lowered the interest rate on the deposit
facility from –0.20 to –0.30 per cent in December 2015 and to –0.40 per
cent in March 2016. The key interest rate on main refinancing operations
was set at 0 per cent (from 0.05%) in March 2016, while the rate on the
1
marginal lending facility was lowered from 0.30 to 0.25 per cent.
The Eurosystem further enlarged the expanded asset purchase
2
programme launched in March 2015. In its December 2015 meeting,
the Governing Council of the ECB decided to extend the horizon of the
expanded APP: it is planned to carry out the programme at least until the
end of March 2017, i.e. for 6 months longer than previously announced. In
addition, the Governing Council announced that the Eurosystem would
reinvest the principal payments being recovered in the market on securities purchased. The current horizon for the expanded APP is 25 months,
but the programme and reinvestment deadlines will depend on whether the
Eurosystem succeeds to achieve the goal of the programme — to return to
a sustainable inflation rate consistent with the primary monetary policy
objective. In the March 2016 meeting, the Governing Council announced
its decision to expand the volume of the monthly purchases of public and
private sector debt securities from the previously announced EUR 60
billion to EUR 80 billion. After the enlargement of the expanded APP, the
total programme volume will reach EUR 1.74 trillion, boosting the Eurosystem’s balance sheet almost 2.3 times.
The public sector purchase programme is the main component of
the expanded asset purchase programme. From March 2015 to April
2016, the Eursosystem purchased debt securities to the value of EUR
871.4 billion, of which bonds of the public sector accounted for 84 per cent,
covered bonds of credit institutions — 14 per cent, and asset-backed
securities — 2 per cent.
5
4
3
LITHUANIAN ECONOMIC REVIEW / June 2016
2
1
0
01/2014
07/2014
01/2015
Average in the euro area
Germany
France
Italy
Spain
Lithuania
Sources: ECB and Thomson Reuters.
07/2015
01/2016
The expanded asset purchase programme reduced bond yields;
however, their dynamics varied since the launch of the programme.
Yields on bonds purchased and their spreads were already low in November 2014, when market expectations about the Eurosystem to launch the
expanded APP were high. Moreover, varying medium-term expectations
about euro area inflation, economic growth, and the Eurosystem’s monetary policy affect bond yields during the implementation of the programme.Therefore; it is not easy to determine the direct effects of the
programme. Yields surged in the second quarter of 2015 following an
increase in inflation and GDP growth forecasts, before falling again in the
third quarter. The latter trend was supported by heightened concerns over
the economic situation in China and other emerging market economies
and their potential impact on the euro area economy, as well as downward
revisions
_________________________________
1
For details about the objectives of negative interest rates, see the Box “Eurosystem’s monetary policy instruments and their application in Lithuania”, Lithuanian Economic Review, June
2015, p. 8.
2
For details about the expanded APP and its objectives, see the Box “Eurosystem’s monetary
policy instruments and their application in Lithuania”, Lithuanian Economic Review, June 2015,
p. 8. Main transmission channels for the expanded APP to stimulate the euro area economy
are described in the Lithuanian Economic Review of December 2015.
In March 2016, the Governing Council of the ECB announced
about thelaunch of the second series of targeted longer-term refinancing operations with even more attractive terms. The second
series of targeted longer-term refinancing operations (TLTRO II) will
provide credit institutions with an even more attractive alternative for
raising long-term credit resources. A total of four operations are planned,
each with a maturity of four years. TLTRO II will be conducted on a quarterly basis, starting in June 2016. Credit institutions will be able to borrow
up to 30 per cent of their loan balance as at 31 January 2016, while the
interest rate will be fixed throughout the term of the operation and equal to
the rate on the Eurosystem’s main refinancing operations (MROs). Credit
institutions, whose net lending will exceed a benchmark, will be subject to
a lower cost of borrowing, tied to the interest rate on the deposit facility.
Credit institutions will be able to repay the amounts borrowed under
TLTRO II before maturity on their own initiative, but will not be required to
do so should they fail to reach the benchmark level of lending to the real
sector as required under TLTRO. In addition, credit institutions already
participating in TLTRO will be allowed to refinance them with new operations — TLTRO II.
Monetary policy measures implemented by the Eurosystem contributed to a decline in interest rates on loans to the real sector and
the narrowing of their spreads across the euro area countries. In
March 2016, the weighted average of interest rates on new loans to nonfinancial corporations was 1.8 per cent, a decrease of 0.9 p.p. from the
end of 2013, while the spread between the highest and the lowest average
interest rate across the euro area countries was 3.3 per cent, a drop of
3
0.6 p.p. The weighted average of interest rates on new housing loans fell
from 3.1 to 2.2 per cent over the same period, while the spread between
the highest and the lowest average interest rate across the euro area
countries dropped from 2.7 to 2 p.p.
In Lithuania, the average interest rate on new loans to nonfinancial corporations and housing loans fell by 0.9 and 0.5 p.p.
respectively from late 2013 to March 2016. In March 2016, the average
interest rate on new loans to non-financial corporations and housing loans
stood at 2.5 and 1.9 per cent respectively. These changes were due to
both a universal downward trend in the interest rates on loans in euro and
the adoption of the euro. During the period, the average interest rate on
loans to Lithuanian non-financial corporations was higher than the euro
area weighted average, as corporations in our country are usually smaller
and consequently face more risks. In contrast, the interest rates on housing loans in Lithuania were lower than the euro area weighted average
during the period. This was largely due to the prevalence of housing loans
with variable interest rates tied to the currently low short-term interbank
interest rates (usually 3- or 6-month EURIBOR), whereas the euro area
weighted average is calculated based on loans with interest rates fixed for
more than 10 years.
The Eurosystem’s accommodative monetary policy has contributed to a recovery in the crediting of the euro area real economy. Based
on the enhanced methodology for adjusting loans for sales and securitisation, which was adopted by the ECB on 21 September 2015, the annual
growth rate of loans to households moved into positive territory in November 2014, while that of loans to non-financial corporations — in July 2015
(after decreasing for three years). In March 2016, the annual growth rate
of loans to households and non-financial corporations in the euro area
_________________________________
3
To minimise the effects of temporary fluctuations and to filter out the trends, loans to nonfinancial corporations and housing loans are analysed using 3-month moving averages.
Non-standard monetary policy measures implemented
by the Eurosystem prompted a decline in interest rates
on new housing loans and their dispersion across the
euro area countries.
9
Chart 8. Average interest rates on new MFI housing loans
Per cent
6
5
4
3
2
1
12/2013
06/2014
12/2014
06/2015
Dispersion across the countries of the euro area
In the euro area
In Lithuania
Sources: ECB and Bank of Lithuania calculations.
12/2015
Note: 3-month moving average; interest rates in Greece have not been included
due to uncommon economic conditions.
Non-standard monetary policy measures implemented
by the Eurosystem have prompted a decline in interest
rates on loans to non-financial corporations and their
dispersion across the euro area countries.
Chart 9. Average interest rate on new MFI loans to nonfinancial
corporations
Per cent
6
5
4
3
2
1
12/2013
06/2014
12/2014
06/2015
12/2015
Dispersion across the countries of the euro area
In the euro area
In Lithuania
Sources: ECB and Bank of Lithuania calculations.
Note: 3-month moving average; interest rates in Greece have not been included
due to uncommon economic conditions.
The Eurosystem’s accommodative monetary policy has
contributed to the recovery of credit to the real sector.
Chart 10. Dynamics of MFI loans to households and nonfinancial corporations in the euro area and Lithuania
Per cent, annual change
6
3
0
-3
-6
-9
-12
2011
2012
2013
2014
2015
To households in the euro area
To non-financial corporations in the euro area
To households in Lithuania
To non-financial corporations in Lithuania
Sources: ECB and Bank of Lithuania calculations.
Note: loan balances were adjusted for the sales and securitisation of loans.
2016
LITHUANIAN ECONOMIC REVIEW / June 2016
of inflation and economic growth forecasts. In April 2016, sovereign bond
yields were lower than in early 2015, although their dispersion increased
somewhat.
10
The effective exchange rate of the euro appreciated
slightly following the depreciation of the currencies in
emerging market economies and some trade partners,
as well as weaker expectations for interest rate increases by the Federal Reserve System.
Chart 11. Real effective exchange rate of the euro and
Lithuanian currency (the litas until 2015 and the euro
afterwards) given differences in the inflation rate across
countries
Index, 01/2011 = 100
115
110
105
100
95
90
85
2011
2012
2013
2014
2015
Real effective exchange rate of the euro area
Real effective exchange rate of Lithuania
LITHUANIAN ECONOMIC REVIEW / June 2016
Sources: ECB and Bank of Lithuania calculations.
2016
stood at 1.6 and 1.1 per cent respectively. In Lithuania, the amount of
loans to households returned to a growth path in the second quarter of
2014, reaching 5.3 per cent in March 2016.The annual fall in the amount of
loans to non-financial corporations decreased to –0.2 per cent in 2015,
and was already positive at the beginning of 2016, with the figure for
4
March standing at 4.6 per cent.
The effective exchange rate of the euro appreciated slightly following the depreciation of currencies in emerging market economies
and some trade partners, as well as weaker expectations for interest
rate increases by the Federal Reserve System. From March 2014 (the
peak value in recent years) to April 2015, the real effective exchange rate
of the euro decreased by 15 per cent; it strengthened until April 2016, but
5
was 9 per cent lower compared to March 2014. The real effective exchange rate of the Lithuanian currency (the litas until early 2015 and the
euro later) had decreased by 12 per cent from December 2014 (the peak
value in the last years) to April 2015, but strengthened afterwards, and in
April 2016 was 3 per cent lower compared to December 2014.
The Bank of Lithuania, which joined the Eurosystem in early 2015,
implements standard and non-standard monetary policy measures,
thereby creating a more favourable environment for crediting and the
development of the national economy, as well as management of the
public debt. Since the beginning of the year, the Bank of Lithuania has
applied to credit institutions operating in Lithuania the minimum reserve
requirement applied by the Eurosystem and offered MROs, longer-term
refinancing operations (LTROs), including TLTROs, as well as two standing facilities — the marginal lending facility and the deposit facility. There
is no market of asset-backed securities or covered bonds in Lithuania and
the Bank of Lithuania does not participate in the purchase programmes of
these securities; however, it has joined the public sector purchase programme. The Bank of Lithuania also buys bonds issued by European
supranational institutions that are eligible for purchase under the expanded
APP, as the amount of debt securities issued by the Lithuanian government is not sufficient to fulfil the requirement for Lithuania — set according
to its capital key — for bond purchases. At the end of April 2016, the
amount loaned to domestic credit institutions via main refinancing operations and LTROs (mostly TLTROs) by the Bank of Lithuania stood at
EUR 348 million, while the amount of public sector debt securities purchased by the Bank of Lithuania over 14 months since the launch of the
expanded APP (from March 2015 to April 2016) — at EUR 3.7 billion.
Since early November 2014, when market expectations regarding the
launch of the expanded APP strengthened, the yields for 10-year shortterm government securities dropped by about 1.5 p.p. or more than twice.
_________________________________
4
A large share of such a significant credit growth at the beginning of the year was driven by one
factor — acquisition of a telecommunications company, financed with bank loans.
5
The real effective rate of the euro is calculated given the inflation rate differences vis-à-vis 38
main euro area trading partners.
III. REAL SECTOR
In the context of rather elevated consumer expectations, household consumption remains a significant driver of economic growth. A
favourable situation in the labour market (both wages and employment
have been rising), the growing purchasing power of households and record
low interest rates on loans (reducing the burden of financial liabilities) are
among major factors behind consumer expectations. They allow households to plan their expenses more optimistically, even though the growth of
disposable income is modest: in the second half of 2015 it increased by
1.1 per cent. Among the components of households’ disposable income,
only compensation of employees has been increasing significantly due to
the favourable labour market situation. This is important, as, out of all
components of households’ disposable income, it has the highest impact
on households’ willingness to consume. In 2015, other components of
households’ disposable income — social benefits, mixed income and
operating surplus — grew slightly or decreased (property income and
current transfers). With sluggish growth in disposable income, households
increase their consumption by saving less and intensifying the use of
services provided by monetary and other financial institutions. The volumes of new consumer loans surged by nearly a third in the second half of
2015. This resulted in a substantial improvement in the net financial flow,
which was used to finance almost one sixth of the increase in households’
consumption.
Despite the quite protracted deterioration in the external environment and weaker economic development, investment growth remains
relatively strong. Especially strong growth is observed in investment in
capital goods. Data on tangible investments shows their increase in a
number of economic activities. Stronger growth of investment in these
goods is related to the need to expand production capacities, observed for
some time, and the use of EU funds, which intensified last year, as the
possibilities for using funds from the EU’s Financial Perspective 2007–
The dynamics of the tradable sector contributed greatly
to the previous deceleration of economic growth and is
well contributing to the current recovery in Lithuania.
Chart 12. Contributions to real GDP by expenditure
approach
Per cent, annual change
9
Percentage points
9
6
6
3
3
0
0
–3
–3
–6
–6
–9
–9
2012
2013
2014
2015
2016
Final consumption expenditure
Domestic investment (excl. inventory changes)
Net exports
Changes in inventories
GDP (rh scale)
Sources: Statistics Lithuania and Bank of Lithuania calculations.
Exporters’ ability to reorientate determines relatively
positive results of the exports of goods and services
amid decreasing external demand.
Chart 13. External demand and real exports of goods and
services (at constant prices, seasonally adjusted)
Per cent, annual change
25
20
15
10
5
0
–5
–10
2012
2013
Extrenal demand
2014
2015
Real exports of goods and services
Real exports of goods and services, excl. mineral products
Sources: ECB and Bank of Lithuania calculations.
Rising compensation for employees contributes to
higher households’ consumption. Other household
income rises marginally or decreases.
Chart 14. Contributions to changes
disposable income (at constant prices)
in
households’
Percentage points
10
Per cent, annual change
10
8
8
6
6
4
4
2
2
0
0
–2
–2
–4
–4
–6
–6
–8
–8
2012
2013
2014
2015
Compensation of emplyoees
Mixed income and operating surplus
Property income
Net other current transfers
Social benefits
Social contributions
Current income, wealth and other taxes
Household disposable income (rh scale)
Sources: Eurostat, Statistics Lithuania and Bank of Lithuania calculations.
LITHUANIAN ECONOMIC REVIEW / June 2016
In 2015, the growth of the domestic economy was the lowest over
the last five years; however, the economic development has already
stabilised and started strengthening somewhat. The tradable sector
has played a significant role in the previous deceleration of economic
growth and its current recovery. Particularly adverse economic developments in the East, both in Russia and other CIS countries, have prompted
exporters’ activity in other regions, primarily in countries with growing
demand for imported goods and services. Transportation enterprises and
re-exporters from the CIS region have started gradually reorientating
towards other markets, primarily the EU. Transportation enterprises are
particularly interested in major Western European markets, such as
France, the United Kingdom, and the Netherlands, whereas the sales of
re-exporters are higher in the neighbouring markets, primarily in Poland.
Stable expansion of the EU economy and strong links with this market also
offer good opportunities for sale for Lithuanian manufacturing enterprises.
In the second half of 2015, their foreign sales income grew by more than 7
per cent over the year, while the increase excluding the sales of refined oil
products accounted for nearly 9 per cent. The highest increase in sales
income was observed in manufacturers of capital goods, furniture and
other wood products. It should be noted that even though Russia is not the
major export market for manufacturers, due to the deteriorating economic
situation in this country, exports of manufacturing products to it accounted
for only 1.7 per cent in the second half of 2015, a year-on-year decrease of
30 per cent. Exporters’s reorientation towards other markets determined
that in 2015 real exports of goods and services, excluding mineral products, shrank less than external demand. Less extensive development of
the tradable sector seems not to have any obvious impact on the development of domestic demand yet — the growth of both household consumption and investments remains robust.
11
12
Despite the external environment, which has been
deteriorating for some time, and weaker economic
development, investment growth remains relatively
strong.
Chart 15. Contributions to investment changes (at constant
prices)
Percentage points
20
Per cent, annual change
20
15
15
10
10
5
5
0
0
–5
–5
–10
–10
2012
2013
2014
2015
LITHUANIAN ECONOMIC REVIEW / June 2016
Housing
Other buildings and structures
Transport equipment
Machinery and other equipment
Other investment and statistical discrepancies
ICT equipment
Gross fixed capital formation (rh scale)
Sources: Statistics Lithuania and Bank of Lithuania calculations.
2013 were coming to a close. The Government’s decision to boost spending for national defence also had a significant effect on investment in
capital goods. The growth of investment in buildings and structures, which
was strong in the first half of 2015, decelerated somewhat in the second
half of the year, unlike the above-named investment in capital goods.
Decreased volumes of the construction of transportation infrastructure,
primarily railway infrastructure, contributed the most to this development of
investment in buildings and structures. Sluggish investment in buildings
and structures led to a slowdown in construction activity in the second half
of 2015 (it should be noted that this economic activity was the major
contributor to economic growth in Lithuania in 2014). The situation may
continue into 2016, as orders from projects financed with EU funds are
expected to be smaller. However, investment in residential construction
has been increasing strongly for the third consecutive year. However,
unlike in 2013 and 2014, when growth was fuelled by new constructions, in
2015 the boost in such contruction was also supported by reconstruction,
restoration and repair works, which were influenced by more intensive
renovation projects.
IV. LABOUR MARKET
The economic situation in Russia and the deteriorating situation in
the construction sector were behind a slightly slower job creation.
However, it remained quite strong, reaching 1.9 per cent in the second half
of 2015. The impact of the situation in Russia on the number of jobs was
marginal. Enterprises within only two economic activities — trade and
transportation — have suffered somewhat negative effects due to it. Notably
fewer jobs were created in them, and this has been the slowest increase in
job creation since the start of the recovery. It should be noted that at the end
of the year, the number of jobs started increasing slightly faster in transportation enterprises, while the situation in trade did not improve. The situation
in the construction sector is worsening: the number of construction enterprises facing insufficient demand is increasing and the volumes of construction works keep decreasing. This was the reason behind a much slower
growth in jobs in the construction sector in the second half of the year,
compared to previous periods. However, in other economic activities, such
as industry and most of services, the situation was good and the number of
jobs was increasing fast.
Shrinking labour force, the growing number of jobs, and the implementation of labour market measures continued to push the unemployment rate down. In the second half of 2015, it stood at 8.9 per cent, a
decrease of 1 p.p. year on year. The biggest decline was seen in the unemployment rate for unskilled individuals. This may have been partially due to
more intensive implementation of measures of active labour market policies.
Nevertheless, the rate of unemployment among unskilled individuals remains very high, at nearly 25 per cent. Most likely, such unemployment is
structural and, therefore, it may not necessarily decrease amid continued
economic growth. It could be reduced by structural reforms. The unemployment rate for other groups dropped less yet it was quite low, standing at 7.1
per cent. The unemployment rates for some occupations were even lower,
standing, for example, at 2.4 per cent for highly skilled professionals.
Quite active hiring, lower unemployment rates and rising minimum
wage determine fast annual wage growth. In the second half of 2015,
wages grew by 6.2 per cent, an increase of 1.3 p.p. from the first half-year.
Wage growth accelerated largely due to the increase of minimum wage by
EUR 25 (to EUR 325) in July 2015. However, most of the growth of compensation was driven by other factors. A rather obvious increase in the
number of both occupied jobs and vacancies shows a considerable need for
new employees, while decreased unemployment rates (especially for skilled
individuals) mean that the supply of employees has diminished. Against this
backdrop, enterprises face a shortage of adequately qualified employees.
Although this shortage is well below the pre-crisis level, it contributes quite
significantly to compensation growth.
_________________________________
6
From 2012 to 2015, excluding 2014, when labour force was growing under the influence of
social support and service voucher reforms as well as other factors.
The higher-than-usual increase in the labour market
participation rate offset the impact of faster decrease
in population on the labour force.
Chart 16. Contributions to labour force dynamics
3
Percentage points
Per cent, annual change
3
2
2
1
1
0
0
–1
–1
–2
–2
2012
2013
2014
Participation rate of persons aged 15–64
Population aged 15–64
Labour force aged 65 or more
Labour force (rh scale)
2015
2016
Sources: Statistics Lithuania and Bank of Lithuania calculations.
Growth in the number of jobs was weaker due to the
downturn in the construction sector and poor
economic situation in Russia.
Chart 17. Contributions to job dynamics
Percentage points
Per cent, annual change
4.0
4.0
3.5
3.5
3.0
3.0
2.5
2.5
2.0
2.0
1.5
1.5
1.0
1.0
0.5
0.5
0.0
0.0
–0.5
–0.5
2012
2013
2014
2015
Construction
Trade and transportation
Other activities
Number of occupied jobs (rh scale)
Sources: Statistics Lithuania and Bank of Lithuania calculations.
Solid demand for labour force, its decreased supply,
and the rising minimum wage determine fast compensation growth.
Chart 18. Wage dynamics
9
Per cent, annual change
8
7
6
5
4
3
2
1
0
2012
2013
Total economy
Public sector
Private sector
2014
Sources: Statistics Lithuania and Bank of Lithuania calculations.
2015
LITHUANIAN ECONOMIC REVIEW / June 2016
The impact of accelerated decrease in the population on labour
force was offset by increased growth in the labour markert participation rate. In the second half of 2015, the labour force contracted by 0.6 per
cent year on year. On average, it declined at this rate almost thoughout the
6
entire recovery period. However, the dynamics of the contributions to the
decrease in labour force in the second half of the year were somewhat
unusual. The labour market (residents aged 15–64) participation rate picked
up slightly more than average during the recovery period, while the pace of
decline in population was the fastest in three and a half years. Migration
trends determined a stronger decline in this indicator. Emigration of people
of both genders and in nearly all age groups increased, while immigration
decreased. Nevertheless, the latest data shows that in the first quarter of
2016 the labour force started growing due to a strong increase in the labour
market participation rate.
13
V. EXTERNAL SECTOR
14
Extremely unfavourable developments in trade with
Russia and other CIS countries undermined export
performance in 2015; however, exports to these regions
have already stabilised.
Chart 19. Lithuania’s exports, excluding mineral products, as
broken down by country groups
Percentage points
Per cent, annual change
15
15
10
10
5
5
0
0
–5
–5
–10
–10
–15
–20
–15
2014
2015
2016
the Baltic States
the euro area, excl. the Baltic States
the EU, excl. the euro area
CIS countries
Other countries
Export (rh scale)
Export, excl. mineral products (rh scale)
Sources: Statistics Lithuania and Bank of Lithuania calculations.
An upturn in oil refining margins led to an increase in
refining capacity utilisation of AB ORLEN Lietuva and
the growth of its ales volumes.
Chart 20. Dynamics of the oil refining margin of AB ORLEN
Lietuva
Euro per barel
12
10
8
6
4
2
0
2008
2009
2010
2011
2012
2013
2014
2015
ORLEN Group refining margins
Long-term average
Sources: ORLEN GROUP and Bank of Lithuania calculations.
Unfavourable export developments, significantly higher
imports and deteriorated balance of primary income led
to the fact that in 2015 the current account balance was
the worst in the last three years.
LITHUANIAN ECONOMIC REVIEW / June 2016
Chart 21. Components of the current account balance
Percentage of GDP
10
5
0
–5
–10
–15
2013
2014
2015
Goods balance
Services balance
Primary income balance
Secondary income balance
Current account balance
Sources: Statistics Lithuania, Bank of Lithuania and Bank of Lithuania calculations.
7
The 2015 export results were weaker than a year ago due to a
sharp decrease in exports to Russia and other CIS countries;
however, exports to these regions have already stabilised. The
nominal value of all exports went down by 5.7 per cent (or by 4.3%, if
mineral products are excluded), while the growth of service exports was
reduced to 2.5 per cent. Such dynamics in exports were determined by
developments in trade with Russia: due to a weaker demand in Russia
and still-effective trade restrictions, exports of goods and services to this
country were approximately one-third lower than a year ago. However, in
mid-2015, exports to Russia stabilised, i.e. exports of goods, to which
restrictions on entry to the country do not apply, and services stopped
falling.
The growth of exports to non-CIS countries has gained momentum. The growth rate of exports of goods, excluding mineral products, to
non-CIS countries stood at about 10 per cent last year, while service
exports to these countries surged by 14 per cent. Early in the year, the
highest upsurge was observed in exports to the EU, while at the end of the
year — in goods exports to far-off countries, such as the US, Saudi Arabia,
the United Arab Emirates, South Korea, India and the Ukraine.
In 2015, Lithuania’s export market share stopped growing (imports of foreign country goods from Lithuania compared to total
imports of goods of these countries) and in some regions it reduced.
Lithuania’s export market share reduced not only in Russia, but also in the
EU, especially in the first half of the year. The market shares of various
product groups exported from Lithuania to the EU went down, yet the
biggest fall was seen in the exports of plastics and their articles, milk and
dairy products, as well as furniture and bedding. Imports of plastics and
their articles grew by 5 per cent across the EU, although their imports from
Lithuania shrank by 14 per cent. Last year, the EU imported less dairy
products, especially from Lithuania. Furniture exports from Lithuania rose
by 4 per cent in 2015, yet total furniture imports by the EU grew by 11 per
cent. Imports grew in various EU countries. At the end of 2015, Lithuania’s
export market share in the EU remained basically unchanged, while its
market share in far-off countries increased significantly.
A spike in the crude oil refining margins has led to improvements
in the mineral product market — an increase in the level of refining
capacity utilisation of AB ORLEN Lietuva and its sales volumes. This
company generated a net profit of EUR 289 million in 2015 — its best
result since 2006, the year of the acquisition of the oil refinery by Poland’s
PKN ORLEN. The oil refining margins of the concerned group of enterprises hiked due to favourable international environment developments for the
mineral product market and the group’s strategy, allowing for faster response to the changing macroeconomic environment.
2015 was the year of especially good harvest and this contributed
to exports. Lithuania exported a large amount of grain to Saudi Arabia,
while peas were sent to India. Although exports grew due to good harvest,
there are signs that agricultural exports may keep increasing further, as
arable land has been growing every year since 2007 and recently the
number of registered agricultural machinery items has increased in all
counties.
In 2015, two factors had a significant impact on the development
of the current account balance. At the beginning of the year the current
account balance deteriorated due to the increased deficit of international
trade in goods. Its growth was driven by a hike in the import of goods,
primarily machinery and equipment, necessary to expand production
capacities, and a decrease in exports of goods due to the already men_________________________________
7
This section reviews nominal foreign trade indicators.
15
LITHUANIAN ECONOMIC REVIEW / June 2016
tioned reasons. However, the balance of trade goods improved at the end
of the year, reaching a similar level observed a year ago.This was one of
the major reasons why the current account balance turned positive at the
end of the year. The second important contributor to the current account in
2015 was a solid deterioration of the primary revenue balance. It deteriorated due to the prolonged growth of income from direct foreign investments. Although the overall amount of direct foreign investments remained
broadly unchanged, some growth was observed in equity-linked direct
foreign investments that depend largely on operational profitability. The
decision of foreign companies to reinvest in Lithuania shows their determination to stay in Lithuania. However, Lithuania’s direct investments abroad
decreased in 2015, leading to a drop in investment-related income from
other countries in Lithuania.
VI. PRICES AND COSTS
16
In 2016, annual inflation in Lithuania returned to
positive territory owing to a reduced impact of the
downturn in fuel prices.
Chart 22. Contributions to annual HICP inflation
Percentage points
Per cent
4
4
3
3
2
2
1
1
0
0
–1
–1
–2
–2
–3
–3
2013
2014
2015
2016
Administered prices
Prices of food, incl. beverages and tobacco
Prices of fuels and lubricants
Prices of services
Prices of industrial goods
Annual core inflation* (rh scale)
Annual inflation (rh scale)
Sources: Statistics Lithuania and Bank of Lithuania calculations.
* Change in HICP, excl. food, fuels and lubricants and administered prices.
The acceleration of annual price growth has been
observed not only for market services but also for
industrial goods.
Chart 23. Price dynamics of industrial goods and market
services
Per cent, annual change
6
5
4
3
2
1
0
–1
–2
2013
2014
2015
2016
Industrial goods and market services
Industrial goods
Market services
Sources: Statistics Lithuania and Bank of Lithuania calculations.
In 2016, consumer prices for food products in Lithuania
picked up slightly, whereas the fall of global food prices
has slowed down.
Chart 24. Food price dynamics
LITHUANIAN ECONOMIC REVIEW / June 2016
Per cent, annual change
10
5
0
–5
–10
–15
In 2015, average annual inflation, as measured by the HICP, accounted for –0.7 per cent. Annual inflation was negative in every month
of 2015 owing to a significant drop in fuel prices which was driven by
decreasing oil prices in global markets. Negative average annual inflation was last observed in 2003, when it was driven by both a considerable fall in prices for telecommunication services, fuelled by increased
competition, and import prices that went down due to exchange rate
developments.
In January 2016, annual HICP inflation entered positive territory
following a more than a year-long deflation, to reach, on average,
0.7 per cent from January to April. These inflation developments were
mostly driven by the already-mentioned fuel prices, since the significant
drop in fuel prices in January 2015 was no longer included in the annual
price change. After an extended period, fuel prices in Lithuania went up
at the end of March this year due to growing Brent crude oil prices that
reached their lows in mid-January 2016. The increase in oil prices from
January to April reflected the slowing US production and expectations for
possible freezing of the oil output level after the April meeting of members of the Organization of Petroleum Exporting Countries (OPEC).
However, the participants of the meeting failed to freeze the oil output
level, thus the growth of oil prices has slowed down. Amid abundant oil
supply, oil prices are hardly expected to rise rapidly this year, and oil
futures indicate that the average crude oil price may stand at USD 43
per barrel in 2016.
Core inflation that is calculated based only on prices of market
services and industrial goods has been increasing since mid-2014.
In 2015, the annual average of core inflation was 1.5 per cent; from
January to April 2016, it stood at 2.3 per cent. This increase has been
mainly affected by rising prices for services (from November 2015 to
April 2016, the average growth rate for services was 4.3%), fuelled by
domestic demand that grew due to positive changes in the labour market
— rising employment and increasing wages. Wages are increasing not
only due to a rising minimum monthly wage, but also a favourable
situation for employees in the labour market, which is related to a
shortage of labour force with appropriate qualifications. Staff costs in the
service sector account for a considerably higher share of total production
expenses compared to other sectors, thus this sector is more sensitive
to wage dynamics. A significant share of employees in the service sector
earns a minimum wage, and this contributes to a larger pressure on
labour costs in this sector. For some time, wages in this sector have
been growing more intensively compared to productivity, which led to an
increase in unit labour costs. In addition to macroeconomic factors, the
introduction of the euro also contributed to the increase in service prices
to some extent. The assessment by the Eurostat published in December
2015 revealed that, due to the introduction of the euro, prices for some
services (such as canteens, the hairdresser’s, rentals for housing,
maintenance and repair of a dwelling) increased, whereas in January
2015, the headline inflation was 0.04 to 0.11 p.p. higher. In Lithuania, the
effect of the euro changeover was lower than in Latvia and Estonia.
–20
–25
2013
2014
2015
2016
Global food prices
Consumer food product prices in Lithuania
Sources: Food and Agriculture Organization of the United Nations, Statistics Lithuania
and Bank of Lithuania calculations.
In the context of recovering domestic demand, prices for industrial
goods began growing gradually in the fourth quarter of 2015 (their
average growth rate was 1.1% from November 2015 to April 2016). Prior
to this, the contribution of industrial goods prices dymanics to annual
inflation was negative or close to zero for a long time.
As expected, prices for food, including beverages and tobacco,
rose slightly in 2016. The annual decrease in global food prices slowed
down as well. According to the data of Food and Agriculture Organization of the United Nations, global food commodity prices went down by
nearly one fifth in 2015, and now their annual fall is close to 10 per cent.
However, consumer prices are affected by other producer costs (such as
wages); hence, changes in food prices are notably smaller than changes
in prices for corresponding commodities. The April 2016 outlook by the
IMF projects yet again a decline in global food prices, although more
modest than in 2015. Global food prices are estimated to fall by 6 per
cent. The forecast refers to high supply (due to high inventories) and
more sluggish demand. Other international institutions have issued
similar forecasts regarding global food price dynamics — a moderate
decline in 2016 and a slow but gradual pick-up in food prices in 2017 are
expected.
17
Increasing excise duties also had a modest effect on food prices in
Lithuania in March this year: excise duties were raised for both cigarettes, in order to gradually reach the minimum excise level in the EU,
and alcoholic beverages.
LITHUANIAN ECONOMIC REVIEW / June 2016
Anticipated trends in commodity prices remain favourable to
consumers, marginal inflation that is projected for the euro area
also allows for small positive inflation expectations in Lithuania.
Various institutions forecast inflation in the euro area to stay in positive
territory but close to zero in 2016. The IMF expects inflation to stand at
0.4 per cent (as announced in April this year), whereas the EC — at 0.2
per cent (the May forecast). The results of the latest ECB Survey of
Professional Forecasters (published in April) also indicate a marginal
inflation of 0.3 per cent. In 2015, inflation in the euro area was
0 per cent.
VII. FINANCING OF THE ECONOMY
18
Recently, businesses and households have more and easier
accesable options to finance their activities and consumption. The
liabilities-to-assets ratio continued to reduce in the private non-financial
sector (non-financial corporations and households), interest rates on
loans stabilised at a low level, and non-price terms of bank loans remained basically unchanged, except for lending to households, which
was tightened when the revised Responsible Lending Regulations came
into effect in November 2015. Moreover, credit institutions’ lending risks
declined due to the improved financial situation of businesses and
households. Against this backdrop, the amount of loans to the private
sector has been growing: from March 2015 to March 2016, the portfolio
of MFI loans to households and non-financial corporations surged by 4.9
per cent. Borrowing from financial lease (leasing) companies has
picked-up as well, with their loan portfolio going up by 18.6 per cent
during the corresponding period.
The portfolio of MFI loans to the private sector has been
growing for some time.
Chart 25. Contributions to changes in the portfolio of MFI loans
to the private sector
Percentage points
6
Per cent, annual change
6
5
5
4
4
3
3
2
2
1
1
0
0
–1
–1
–2
–2
–3
–3
–4
–4
2012
2013
2014
2015
2016
Households
Non-financial corporations
Private non-financial sector (rh scale)
Households were the most active in getting financing from
credit institutions. In March 2016, the portfolio of MFI loans to households surged by 5.3 per cent year on year. Its growth was driven mainly
by housing loans, however, portfolios of consumer loans and loans for
other purposes increased as well. A low level of interest rates on loans
to households prevents them from a significant fall. In March 2016,
variable interest rates on loans for house purchase stood at 1.79 per
cent — slightly above the average in 2015. The growth of employment
and wages in 2015 boosted residents’ confidence in the economic
situation and improved household financial situation, which resulted in a
higher number of households purchasing durable goods (such as a
home or a car). Such purchases contribute to the growth of bank loan
portfolio as borrowed funds are used to finance them. Moreover, house
purchases may have been prompted by low interest rates as the return
on savings in banks in the form of deposits reached a record low and
encourages looking for alternative ways to use money. The Revised
Responsible Lending Regulations, which came into effect on 1 November 2015, could have also contributed to a more rapid growth of housing
loans. In anticipation that these amendments would probably make it
more difficult to qualify for a housing loan, households could have
considered purchasing a house before the amendments came into
force.
Sources: Bank of Lithuania and Bank of Lithuania calculations.
Interest rates for loans to households and businesses
have stabilised at a low level.
Chart 26. Interest rates
Per cent
6
5
4
3
2
1
0
–1
2012
2013
2014
Variable interest rates on housing loans
2015
8
2016
Variable interest rates on business loans up to EUR 1 million
3-month EURIBOR
Sources: ECB and Bank of Lithuania.
The portfolio of loans to non-financial corporations
continues to increase due to lending by trade, energy and
transportation sectors.
Chart 27. Loans by economic activity
Percentage points
8
6
8
4
6
4
2
2
0
0
–2
LITHUANIAN ECONOMIC REVIEW / June 2016
After a long period of decline, the portfolio of loans to businesses started to grow. In March 2016, the portfolio of MFI loans to
non-financial corporations grew by 4.6 per cent year on year. It was
strongly affected by the merger of two major telecommunication companies in January 2016. EUR 150 million was borrowed from Lithuanian
banks to finalise the deal. The money was used to pay a Swedish and
Finnish telecommunication concern for the shares rather than finance
Lithuania’s economy. Nonetheless, the portfolio of loans to non-financial
corporations would have grown by 2.5 per cent even without the deal. In
the first quarter of 2016, the biggest contributors to its year-on-year
growth were loans to transportation and storage enterprises and energy
supply operations. Portfolios of loans to these economic activities grew
by 28.9 and 13.5 per cent respectively. The demand for loans to transportation and storage enterprises might have been prompted by the
need to finance expansion to new markets. It is likely that the creation
and renovation of energy infrastructure has contributed to the growth of
the portfolio of loans to the energy supply sector. Nonetheless, the
Per cent, annual change
10
–2
–4
–4
–6
–6
–8
–8
–10
–10
2013
2014
2015
Remaining activities
Transportation and storage
Construction
Trade
Real estate activities
Energy supply
Manufacturing
Loans to business (rh scale)
Sources: Bank of Lithuania and Bank of Lithuania calculations.
2016
_________________________________
8
In order to evaluate loans, this section includes MFI data provided by the Statistics
Department of the Economics and Financial Stability Service of the Bank of Lithuania, which is
adjusted taking into account bankruptcies and mergers in the sector concerned (for more
details, see Annex 2 of the Lithuanian Economic Review, December 2014). This data may
differ from the data collected from banks for supervision purposes.
process of business deleveraging has continued as well. In 2015, the
year-on-year growth of their equity, which outpaced the growth of their
liabilities, helped enterprises to decrease their financial leverage by
2.2 p.p. to 67.8 per cent.
19
LITHUANIAN ECONOMIC REVIEW / June 2016
Currently, possibilities for financing operations of enterprises
are generally good. Such statement is possible because of a low cost
for borrowing from credit institutions and a possibility to use alternative
financing sources (such as accrued profit from previous periods, funds of
stockholders), though bank lending conditions remained broadly unchanged. Recently, the number of enterprises reporting operational
restrictions due to financial difficulties continued to decline, whereas in
the first quarter of 2016 the share of such enterprises in the industrial,
service and contruction serctors was the lowest in the last ten years, in
the retail trade sector — the lowest in the last eight years. In February
2016, the average variable interest rate on loans up to EUR 1 million to
non-financial corporations reached 2.52 per cent — the lowest level
since the start of the series.
VIII. GENERAL GOVERNMENT FINANCES
20
In 2015, general government deficit, when adjusted for
one-off factors, was slightly lower year on year.
Chart 28. General government revenue, expenditure and
balance when adjusted for one-off factors (4-quarter moving
sum)
Percentage of GDP
45
Percentage of GDP
3
42
0
39
–3
36
–6
33
–9
30
–12
2012
2013
2014
2015
Revenue (adjusted for one-off factors)
Expenditure (adjusted for one-off factors)
Balance (adjusted for one-off factors, rh scale)
Source: Statistics Lithuania and Bank of Lithuania calculations.
Higher revenue, slower real GDP growth and the price
level had a substantial effect on the general government
revenue-to-GDP ratio in 2015.
Chart 29. Contributions to the general government revenueto-GDP ratio (taxes and social contributions, 4-quarter
moving sum)
Percentage points
3
2
1
0
–1
–2
–3
–4
2012
2013
2014
2015
Contribution of the change in the GDP deflator
Contribution of the change in real GDP
Contribution of the change in GG tax revenue and social contributions
Calculation error
Change of the ratio of the sum of the GG tax revenue and social contributions to GDP
Source: Statistics Lithuania and Bank of Lithuania calculations.
For a prolonged period robust domestic demand
continued to be the major driving force behind general
government revenue growth.
Chart 30. Contributions to general government revenue
Per cent, annual change
LITHUANIAN ECONOMIC REVIEW / June 2016
Percentage points
15
15
10
10
5
5
0
0
–5
–5
–10
–10
2012
2013
2014
2015
Indirect taxes
Social contributions
Taxes on income, wealth, etc.
Non-tax revenue
Total revenue (rh scale)
Sources: Statistics Lithuania and Bank of Lithuania calculations.
In 2015, the situation of general government finances improved significantly: the ration of the general government balance to GDP accounted for –0.2 per cent and was the lowest
since the start of the time series in 1999. The Republic of Lithuania
Law on the Approval of Financial Indicators of the State Budget and
Municipal Budgets of 2015 set the general government deficit at 1.2
percent of GDP. It shrank more than planned due to higher revenues
and lower expenditure: in 2015, the general government revenue-toGDP ratio was 0.5 p.p. higher, whereas spending went down by
0.5 p.p. compared to the figures in the 2015 Stability Programme for
Lithuania. Ratios of direct taxes, social contributions and other revenues to GDP were higher than expected, while the ratio of indirect
taxes to GDP was lower than planned largely due to the underexecution of the VAT revenue plan. Lower social benefits, interest rates paid
and other spending stood behind the lower-than-expected ratio of
spending to GDP.
When adjusted for one-off factors, the 2015 general government deficit was slightly higher, accounting for about 0.6 per cent
of GDP. Various one-off factors had an impact on the general government balance in 2015. The impact that VĮ Indėlių ir Investicijų
Draudimas made on the 2015 general government balance was
positive, standing at approximately 0.6 per cent of GDP. However,
spending on the compensation of wages to civil servants had a negative effect on the general government balance — it accounted for
about 0.2 per cent of GDP. Last year, the combined impact of the said
factors on the general government balance was overall positive,
standing at around 0.4 per cent of GDP.
Increased domestic demand, slower real GDP growth and low
inflation were major reasons behind the increase in the ratio of
general government revenues to GDP. In 2015, general government
revenues grew faster than nominal GDP, therefore, the revenue-toGDP ratio picked up by 0.8 p.p. over the year — to 34.9 per cent. In
2015, the contribution of general government revenue growth to the
change in the revenues-to-GDP ratio was approximately the same as
in the previous year, but the negative impact of changes in real GDP
and the general price level was considerably smaller.
In the second half of 2015, the nominal value of general government revenues increased by more than 3 per cent year on
year, yet the performance of individual revenue items differed.
The growth in revenues was largely driven by social contributions and
income from direct taxes that increased compared to the previous
year. This income surged due to a significant rise in wages and higher
employment rates. The latter factors had a positive effect on households’ consumer spending, while their increase and one-off factors,
such as the rise of excise tariffs for processed tobacco and alcoholic
beverages on 1 March 2015, created conditions for the growth of
general government revenues from indirect taxes. However, the
positive impact of higher domestic demand on general government
revenues was offset by revenues from capital transfers that fell by
nearly a third. They dropped as a result of a high comparative base:
government sector revenues from the operations of VĮ Indėlių ir
Investicijų Draudimas amounted to around EUR 330 million in the
second half of 2014, and to about half of that amount in the second
half of 2015.
The ratio of general government expenditure to GDP jumped
up to 35.1 per cent after it increased nearly by one tenth in the
second half of 2015. In the second half of the year, the incease in
general government spending was driven mainly by higher spending
on intermediate goods and services, as well as higher compensation
for employees and social benefits. The amount of social benefits
picked up as a result of higher sickness and maternity leave benefits
(compared to the previous year), as well as larger unemployment
insurance benefits and spending on pension payments. The latter
grew following the government decision of July 2015 to increase old
age pensions. Sickness and maternity as well as unemployment
benefits increased due to the restoration of these benefits to the precrisis levels, as laid down in the budget of the State Social Insurance
Fund for 2015. Lower spending on interest payments was the major
driving force behind the decrease in total spending in the second half
of 2015. In 2015, they were decreasing for the third consecutive year.
The fall in interest is led by large earlier bond issues that were refinanced under more favourable conditions in a low interest rate
environment, as well as government credit ratings that improved due
to sustainable economic development.
Government sector expenditure growth was driven
mainly by higher intermediate consumption, compensation to employees which increased due to the faster
growth of wages, and social payments that grew as a
result of discretional decisions of the government.
The general government debt-to-GDP ratio increased to 42.7
per cent in the second half of 2015. Nominal debt increased by EUR
2.1 billion (5.6% of GDP) in the second half of 2015 largely due to the
growth of the portfolio of long-term government securities after the
placement of the EUR 1.5 billion (4.0% of GDP) bond issue in October,
a significant part of which was used to redeem securities at the beginning of 2016. Moreover, the long-term loan portfolio increased as well.
Chart 32. Contributions to the general government debt-toGDP ratio
Chart 31. Contributions to general government expenditure
Percentage points
15
Per cent, annual change
15
10
10
5
5
0
0
–5
–5
–10
–10
2012
2013
2014
Social payments
Interest
Compensation of employees
Intermediate consumption
Total capital expenditure
Other consumpion
2015
Sources: Statistics Lithuania and Bank of Lithuania calculations.
In 2015, there were only a few favourable macroeconomic factors dampening the debt-to-GDP ratio.
Percentage points
15
Percentage of GDP
45
10
40
5
35
0
30
–5
25
20
–10
2009
2010
2011
2012
2013
2014
2015
"Snow ball" effect ((r-g)/(1+g))
Deficit-debt adjustment*
Primary balance-to-GDP ratio
Change of debt-to-GDP ratio
Debt-to-GDP ratio (rh scale)
Sources: Statistics Lithuania and Bank of Lithuania calculations.
*Includes other debt affecting factors that are not included into the general
government balance.
LITHUANIAN ECONOMIC REVIEW / June 2016
In 2015, there were few macroeconomic factors that dragged
the debt-to-GDP ratio down. Positive net lending that, in absolute
terms, was higher than the general government deficit was one of the
major driving forces behind the increase of the general government
debt-to-GDP ratio in 2015. The decrease in the debt ratio did not
decrease also due to the unfavourable interest rate growth differential
(the “snowball effect”). The latter factor led to a hike of the general
government debt-to-GDP ratio after a four-year break. A higher than a
year ago surplus of the general government primary balance was the
only favourable macroeconomic factor in 2015.
21
22
ANNEXES
ANNEX 1. Non-standard monetary policy measures of the ECB
1. Why non-standard measures in the first place?
Standard or conventional monetary policy primarily refers to a stated price-stability objective of a central bank (most of
the time in the form of a target inflation rate) along with the tools employed to achieve the stated objective. In order to
implement standard monetary policy, the major central banks normally steer short-term interest rates by signalling monetary
policy stance and managing banking system liquidity (Borio, 1997). Signalling provides economic agents with a clear
statement about the desired monetary policy stance of the central banks. Most of the time, the stance is identified as a
policy operating objective — a level or range of selected short-term market interest rates which is estimated to be consistent with the price stability objective (ranging from the euro overnight rate EONIA for the European Central Bank to the
three-month Swiss franc LIBOR for the Swiss National Bank).
The prevailing interest rates are compared to a desired rate and the central bank achieves the desired interest rate level
primarily through liquidity operations. Following the 2007–2008 financial crisis, through communication about the desired
current and future level of interest rates, central banks also guides the expectations of economic agents of future policy
rates. The policy rate is related to a Taylor rule-like function, where the level of interest rates depends on two factors: the
state of inflation relative to the assumed inflation objective and the level of output relative to potential output. Liquidity
management operations refer to the operations undertaken by central banks in balancing the level of bank reserves with the
aim to avoid significant and prolonged deviations of the short-term rate from the target rate. Through open market operations, the central bank will inject or extract liquidity in the system so as to perfectly match the demand from the banking
system. This is normally done by lending bank reserves against eligible collateral. The primary mechanism relies on repurchase transactions between the Eurosystem providing liquidity and a credit institution securing the funds with high-quality
collateral.
The financial crisis of 2007–2008 impaired the financial intermediation and credit creation functions of the banking sector and led to a dramatic reduction in the ability and willingness of commercial banks to finance the real sector. Firms and
households faced difficulties in borrowing for either investment or consumption. Banks needed large injections to improve
their liquidity and solvency in repairing their balance sheets and metabolising the effects of the crisis rather than extending
financing and credit to the real sector. Commercial banks’ reluctance to lend crippled the interest-rate transmission channel.
In an effort to support economic growth, target interest rates were gradually lowered down to their nominal zero bound.
Central banks became constrained in their capacity to pass lower rates to the real sector beyond this level. The Taylor-rule
implied interest rates may be below zero given low levels of inflation and economic activity, yet large negative rates may
face implementation challenges in the market. This occurs when firms and households have the ability to hold cash balances rather than deposits (Bech and Malkhozov, 2016) and when demand for credit and financing does not materialise at the
level needed to rid the economy of the inauspicious consequences of the financial crisis.
LITHUANIAN ECONOMIC REVIEW / June 2016
The conventional tools at the disposal of central banks have thus become less effective in conducting monetary policy.
This has brought about the need for alternative or non-standard measures. It should be stressed that the choice of nonstandard tools has been conditioned by the nature and effects of the 2007 –2008 crisis. The need to ensure, in the first
stage, a minimum of functionality in the banking sector and financial markets as well as the need to stem liquidity-driven
asset sales transformed central banks into financial intermediaries taking on their balance-sheet both public and private
debt as well as other risky assets. The subsequent lowering of the target rate to the zero bound forced central banks to look
at interest rates beyond the short-term rates. The different degree of financing of the economy by the banking sector further
explains the difference in choice and intensity of the use of non-standard tools between the ECB and the FED. The ECB
had to replace a comparatively larger volume of bank credit and financing intermediation than the FED as economies in the
euro area are much more reliant on the banking sector than the regional counterparties in the US.
2. What is unconventional about the current monetary policy measures?
To overcome the impairments in monetary policy transmission and concerns associated with reaching the zero lower
bound, central banks altered the mix and scope of tools used to achieve their price stability objective. The measures won
their reputation as non-standard as, in the case of the FED and the Bank of England, the focus was shifted from a policy
rate (standard monetary measure) towards changes in the structure and nominal increases of their respective balance
sheets — thus earning the name of quantitative easing. Regarding ECB’s actions, one may distinguish two qualitatively
different phases: the early response to crisis (including the financial and sovereign crisis) and a second period characterised by low uptake of credit, slowly growing consumption and investment as well as increasing fears of deflation. If the first
phase (Phase I) is concerned primarily with the well-functioning of the financial sector and ensuring the transmission of the
monetary policy stance (Cour-Thimann, 2012), the second phase (Phase II) is driven mainly by developments in the real
sector and the evolution of expectations of economic agents (households, firms and commercial banks). The nature and
extent of unconventional measures reflect the relatively different underlying drivers of the two phases and their interplay
with the prevalent institutional frameworks.
2.1. Unconventional measures of the ECB: Phase I
23
More than 70 per cent of the financing needs of the non-financial corporate sector in the EU are provided by the banking sector with an even higher proportion in the case of households. Given large volumes of tangible collateral and long
histories of economic activity reflected in public accounting numbers, large corporates have the ability to tap the capital
markets should the banking sector curtail credit or financing. This possibility is not available for a large share of SMEs,
firms that account for the bulk of employment in the EU. Banks are, therefore, essential not only in ensuring smooth
transmission of the policy rate decision of the ECB but also in promoting sustainable growth through proper financing of a
very large number of economic agents.
Phase I (August 2007–September 2012) debuted with increased strains in the money markets. Commercial banks’
lending and borrowing activities in the interbank market are conducted on an uncollateralised basis, trust in the solvency
and liquidity of the counterparties being sufficient to allow day-to-day operations. In August 2007, following the fund
withdrawal freeze announcement of BNP Paribas, money market spreads (the difference between EURIBOR and overnight index swap rates) increased dramatically in the span of a few days, signalling a loss of counterparty trust (Cassola
and Morana, 2012). Commercial banks faced increased costs in securing short- and medium-term liquidity in the interbank market threatening not only lending to the real economy, but payment settlements as well. The monetary policy
stance of the ECB is directly conveyed through changes in the main refinancing rate (MRO). This is the signal driving
changes in the EONIA rate (the euro overnight index rate) and the EURIBOR rate used by banks to borrow and lend from
each other in the unsecured market. A potential decoupling of the EONIA from the MRO implied that the monetary policy
stance would no longer be clearly conveyed to the banking sector and, in turn, to lending and deposit rates for economic
agents. Moreover, the failure of Lehman Brothers caused an increased possibility of bank deleveraging through asset
sales (in the form of concomitant sales of government bonds and other assets), a gridlock of the securitised market (the
valuation difficulties of securitised assets was greatly increased by the lack of liquidity) and a virtual standstill of lending to
the real sector.
Hence the first unconventional measures of Phase I have been aimed primarily at restoring the normal functionality of
the banking system as a conduit of the monetary policy stance. The measures have been designed and implemented to
tackle the situations highlighted before — restoring liquidity and removing uncertainty regarding future liquidity conditions
and credit availability. The set of measures has been dubbed by the ECB as the enhanced credit support.
The liquidity-improving measures have also had some second-order positive effects in improving the capital position
of credit institutions (see, for example, Heider et al., 2010). This enhanced the bank capital channel, unlocking the supply
of loans to the broader economy. The bank capital channel posits that better capitalised banks will have a higher supply
of loans. The authors indicate that for Spain both monetary policy (through higher short-term interest rates) and the
business cycle (lower GDP growth) reduce the supply of credit. These effects are stronger for banks with weak capital
and liquidity positions. The authors provide evidence in favour of the importance of the bank capital channel using individual loan applications from the Credit Register of Spain matched against the granting banks’ balance-sheet characteristics. Separating loan demand from loan supply determinants, the authors found that both bank capital and bank liquidity
ratios are important factors in the loan-granting decision. Higher short-term interest rates (associated with a tightening in
monetary policy) or lower GDP growth rates reduce the probability that a loan application is accepted. On top of this, the
lower the capital or liquidity level of the processing bank, the higher the negative effects from higher interest rates. When
th
comparing weak and strong banks (where weak banks are defined as being in the 10 percentile of capital and liquidity
th
levels, strong banks being in the 90 percentile of capital and liquidity), an increase in the interest rate affects weak
banks comparatively stronger than strong banks. Following 100 basis points increases in the interest rate, weak banks
will decrease their loans 11 per cent more than the strong banks. Lack of liquidity and capital availability at the bank level
may thus lead to a credit reduction to the real economy. The results reflect the operation of the bank lending channel up
to 2008 (the authors indicate using data up to 2010 as robustness check). It is uncertain if asymmetric effects may be
LITHUANIAN ECONOMIC REVIEW / June 2016
Several changes have been implemented to ensure an effective transmission of the policy stance (ECB, 2010). If prior
to Phase I central bank liquidity was auctioned in a fixed amount in a variable rate tender, during Phase I the ECB
changed to a fixed-rate full allotment procedure in order to meet liquidity requirements of bidding institutions. This was
aimed at improving the interest-rate channel, the process through which policy rates are transmitted to short-term interest
rates and, subsequently, to investment-relevant long-term rates. In addition, maturities of liquidity operations were prolonged (long term refinancing operations saw their maturities go up to 12 months from 3 months prior) and eligibility
criteria for collateral pools were changed. The list of counterparties allowed to participate in these operations was expanded as well. At the same time, the ECB launched a programme to unlock the covered bond market. The malfunctioning of this market segment caused an inability of valuation, transaction and new issuance in covered bonds. Through the
covered bond purchase programmes (CBPPs), the Eurosystem became the buyer of last resort, unlocking thus a vital
financing source for banks, while at the same time improving market transparency. Currency swap agreements with the
FED and the SNB provided foreign currency liquidity against euro-denominated collateral. As a result of these measures,
liquidity of banks improved considerably. This did not initially translate in a one-to-one change in lending as banks engaged to some degree in liquidity hoarding, the levels of daily liquidity surpluses went up from an average of EUR 10
billion per day to well over EUR 100 billion per day. As a result, the EONIA rate moved close to the lower band of the
target rate range. Figure 1 provides a schematic representation of the inter-bank market freeze.
24
present, if similar size decreases in the interest rates are expected to produce the same magnitude changes in lending.
Ciccarelli et al. (2015) indicate that these results are heterogeneous across bank and borrower sizes, highlighting the role
and importance of the firm and household balance-sheet channel. As small banks lend to small firms, weakness in the
balance-sheets of this duo will greatly amplify shocks from the bank credit channel (Ciccarelli et al., 2013).
The second part of Phase I started with an emphasis on sovereigns and their solvency. As the banking regulatory
framework attached zero risk weights on holdings of sovereign debt commercial banks were not required to set aside any
risk capital for investment in sovereign fixed income securities. This factor, together with the high liquidity and wide acceptance in central bank lending, caused a high concentration of sovereign exposure in most banks. The potential weaker
economic growth leading to lower tax revenues along with the possible need to recapitalise distressed banks cast doubt on
the riskless nature of sovereign debt. The expectations of an imminent Greek government default accelerated these mechanisms, bringing under close scrutiny the fiscal position of other countries as well (Portugal, Ireland, Spain and Italy). This
set in motion a vicious feedback loop whereby banks located in the previously mentioned countries, holding large amounts
of sovereign bonds, increased the probability of rescue through tax-payer contributions and hence led to higher default
likelihood of government bonds. This raised borrowing costs for sovereigns further depressing their valuations, weakening,
in turn, the balance sheet of banks. At the same time, in order to maintain the integrity of their balance-sheets, banks
curbed lending and required higher quality collateral. Figure 1 indicates how this mechanism operates. To stop the operation of this loop, the ECB engaged in purchases of government debt under the Securities Market Programme (SMP),
extended LTROs maturities to 3 years and established the Outright Monetary Transactions (OMT) programme to further
purchase government bonds conditional on fiscal adjustments. The OMT programme is an instance of successful communication strategy, relieving the policy institution of the need to actually intervene in the markets. Also, collateral eligibility
criteria were relaxed, allowing national central banks to accept bank loans.
LITHUANIAN ECONOMIC REVIEW / June 2016
Figure A. A simplified representation of the cascading effects of the breakdown in the interbank market
These programmes were aimed at ensuring that liquidity remained ample while at the same time addressing the then
emerging premium associated with redenomination risk — the possibility that the issuing country under distress would opt
to leave the euro area, forcing the reconversion of the euro-denominated debt in a local currency (at an unfavourable rate).
Krishnamurthy et al. (2015) use an event study to test whether the SMP, OMT and LTRO had the expected consequences
and document the channels through which these programmes alleviated market stress. The authors show that the SMP and
the OMT induced a substantial decrease in the government bond yields, while the LTROs produced relatively lower impact
on yields. The analysis is carried out by disentangling the individual country yield level in two distinct groups:
- Euro-area common components: an expectation hypothesis component and a euro-rate term premium;
- Country specific components: default risk premium (the premium expected by investors to compensate for the
possibility of default), redenomination risk (the premium expected by investors to compensate for the possibility of redenominating the bond in a depreciated local currency) and market segmentation (valuation differentials caused by the different constraints of investors).
The study shows that the first group carries little weight in explaining the changes in yields, while the second represents the main channel of operation of the SMP and OMT. For example, two days after announcements regarding SMP
purchases, Italian 2-year sovereign bond yields decreased on average by 183 basis points, while Portuguese 2-year
sovereign bond yields decreased by 550 basis points. OMT announcements are estimated to have produced, by and
large, similar decreases in yields from an average decrease of 248 basis points for Spain to 74 (statistically insignificant)
for Portugal. The authors also found that the programmes had spill-over effects increasing equity pricing in both core and
non-core countries.
25
Figure B. A simplified representation of the negative feedback loops in the economic system
In 2014 the ECB announced new stimulus measures, expected to address the persistently weak inflation outlook and
the sluggish economic recovery. The TLTRO programme was launched, allowing commercial banks to finance their
operations over a period of up to 4 years subject to a fixed interest rate. The borrowing limits were set in accordance with
their stock of eligible loans and, later on, with the net lending amounts to non-financial corporations and households
(excluding mortgages). This measure allowed banks to replace interbank and market funding sources with stable fixedcost Eurosystem financing. It brought a higher degree of certainty as far as bank funding is concerned, matching better
the duration of liabilities to that of assets. An APP was launched. The APP is composed of three elements: the covered
bond purchase programme 3 (CBPP3), the asset-backed securities purchase programme (ABSPP) as well as a module
focusing on purchases of public sector securities through the public sector purchase programme (PSPP). The PSPP is
the Eurosystem’s equivalent of a Quantitative Easing programme. The PSPP has been an essential change in monetary
policy implementation towards pro-active large-scale purchases instead of passive reliance on bank demand for lending
facilities as witnessed in the programmes launched before it. The ABSPP provided a certain demand source for eligible
asset backed securities allowing banks to reactivate their activity in securitisation and selling loans.
The primary target of the TLTRO was to ensure that the accommodative monetary policy stance is better reflected in
the borrowing costs of final users of credit. Previously, the risk averse behaviour of commercial banks led to liquidity
hoarding and very little lending, preventing the pass-through of lower funding costs into lower lending rates. These effects
have been more pronounced in the countries under sovereign and intense firm and bank balance sheet distress. The 125
basis points reduction in the MRO rate over 2011–2014 has translated in a median decrease of 92 basis points for
Germany and France but only a median decrease of 28 basis points for Ireland, Spain or Italy. Following the announce-
LITHUANIAN ECONOMIC REVIEW / June 2016
2.2. Unconventional measures of the ECB: Phase II
26
ment of the Phase II package, the reduction in borrowing costs has been higher in GIIPS countries (113 basis points) as
compared to the rest of the euro area (50 basis points) (see ECB 2015). The APP is estimated to have reduced sovereign
bond yields by as much as 80 and 78 basis points for Spanish 10- and 20-year bonds (statistically significant estimate) and
as little as 13 basis points (statistically insignificant estimate) for the German 20-year bonds. Beneficial spillover effects
include a 200 basis points increase in the Dow Jones Euro Stoxx as well as a decrease in corporate spreads of 63 and 50
basis points for financial and non-financial corporations respectively (Altavilla et al., 2015).
The more intense reliance on ECB funding was matched by a lower use of traditional market-based funding — issuance
of debt securities and interbank borrowing. A lower supply of debt securities, given constant or increasing demand raised
their price, improving thus the balance-sheet positions of firms and households holding these assets. The lower the holding
of fixed-income securities by households is, the lower the potential wealth-induced benefits are. Moreover, the wealth effect
is expected to work more for gains perceived to be less volatile over time, such as those from house price appreciation as
opposed to equity markets or bond markets during distress periods (Lettau and Ludvigson, 2004).
When the Eurosystem purchases government or private bonds, it pays for the assets by creating central bank reserves.
These reserves remain within the banking system if the seller is a bank (changes in bank asset side only) or become a
deposit if the seller is a private individual (deposits+100 | bank reserves+100). Through its acquisitions of both private and
public bonds, the above-mentioned programmes have thus altered the structure of portfolios held by the private sector (as
well as the balance-sheet of the ECB itself). These changes in the composition of portfolios, exchanging longer maturity
assets (such as public or private bonds) for shorter maturity assets (such as cash or reserves), may affect the yield on still
other assets due to the imperfect substitutability of assets. As cash or deposits are not a perfect substitute for the sold
assets, economic agents seek to acquire similar maturity/duration assets in the market. In their search for alternatives, they
bid up prices and thus lower the financing costs for those companies or industries (Joyce et al., 2012). This is the portfolio
rebalancing channel. One issue that remains open is whether the extra credit risk coming from purchasing commercial debt
as a substitute for similar maturity government debt is properly hedged. Of interest are also the economic implications for
banks, pension plans and insurance companies deriving from setting aside higher capital charges associated with such
purchases as required in a standard ALM risk management framework (Basel III or Solvency II).
References
Altavilla C., Carboni G., Motto R. 2015: Asset Purchase Programmes and Financial Markets: Lessons from the Euro
Area. ECB, Working Paper Series, No. 1864.
Bech M. L., Malkhozov A. 2016: How Have Central Banks Implemented Negative Policy Rates? BIS Quarterly Review,
March.
Borio C. 1997: The Implementation of Monetary Policy in Industrial Countries: A Survey. BIS Economic Papers, No. 47.
Cassola N., Morana C. 2012: Euro Money Market Spreads during the 2007-? Financial Crisis. ECB Working Paper
Series, No. 1437.
Ciccarelli M., Maddaloni A., Peydro J. L. 2013: Heterogeneous Transmission Mechanism: Monetary Policy And Financial
Fragility in the Eurozone. – Economic Policy 28, 459–512.
Ciccarelli M., Maddaloni A., Peydro J. L. 2015: Trusting the Bankers: A New Look at the Credit Channel of Monetary
Transmission. – Review of Economic Dynamics 18, 979–1002.
Cour-Thimann P., Winkler B. 2012: The ECB’s Non-Standard Monetary Policy Measures: The Role of Institutional
Factors and Financial Structure. – Oxford Review of Economic Policy 28(4), 765–803.
LITHUANIAN ECONOMIC REVIEW / June 2016
European Central Bank (ECB) 2010: ECB Monthly Bulletin, October.
European Central Bank (ECB) 2011: ECB Monthly Bulletin, July.
European Central Bank (ECB) 2015: ECB Monthly Bulletin, November.
Heider F. Hoerova M., Holthausen C. 2010: Liquidity Hoarding And Interbank Market Spreads: The Role Of Counterparty Risk. ECB Working Paper No. 1126.
Jiménez G., Ongena S., Peydro J. L., Saurina J. 2012: Credit Supply and Monetary Policy: Identifying the Bank BalanceSheet Channel with Loan Applications. – American Economic Review 102(5), 2301–2326.
Joyce M., Miles D., Scott A., Vayanos D. 2012: Quantitative Easing and Unconventional Monetary Policy – An Introduction. – The Economic Journal 122, F271–F288.
Krishnamurthy A., Nagel S., Vissing-Jorgensen A. 2015: ECB Policies Involving Government Bond Purchases: Impact
and Channels, Working Paper.
Lettau M., Ludvigson S. C. 2004: Understanding Trend And Cycle in Asset Values: Reevaluating the Wealth Effect on
Consumption. – American Economic Review 94(1), 356–366.
27
ANNEX 2. Differences in average compensation for employees across the Baltic States
Economic development levels of the Baltic countries are very much alike, however, significant differences can be observed in the average compensation of employees at current prices. Different structure of the disposable income of
households is one of the factors that explain these differences. It shows that compensation of employees, as a share of
total disposable income, is lower in Lithuania than in other Baltic countries. This Annex presents a comparison between
the ratio of Baltic countries’ labour productivity to compensation of employees, measured in purchasing power parity
(PPP) terms, and the same ratio in other EU countries. The analysis reveals that the ratio is broadly in line with the EU
underlying pattern.
1.
Compensation of employees and disposable income
9
Since 2012, the average nominal compensation per employee which includes a wage and social contributions has
been growing in Lithuania, on average, by 4.5 per cent a year. Such growth pace is slower than the growth of the average
compensation per employee in Latvia and Estonia. In Lithuania, the average compensation per employee is not only
growing at the slowest pace, but is also the lowest. For instance, in 2015, the average monthly compensation per employee in Lithuania was EUR 1,087, in Latvia it was EUR 1,137, and in Estonia — EUR 1,453. It means that Lithuania’s
average compensation per employee was 5 per cent lower than compensation paid in Latvia, and even one third lower
compared to the compensation in Estonia (see Chart A). However, compensation of employees makes up only a part of
household income. Households also receive income from economic activity, accrued capital, government institutions, and
remittances from family members abroad. All these and other income sources are classified under households’ disposa10
ble income , i.e. all income received by households, which is available after compulsory liabilities are paid. As seen in
Chart B, disposable income of households per capita in Lithuania and Estonia have been quite similar since 2010: in
2014, disposable income per capita in Lithuania was lower than disposable income per capita in Estonia only by 5 per
cent (and exceeded the respective indicator in Latvia by more than 10%).
Chart A. Average monthly compensation per employee in the Baltic
countries
(at current prices)
Chart B. Average monthly disposable income per capita in the Baltic
countries
(at current prices)
Euro
Euro
1,500
700
650
1,300
600
550
1,100
500
450
900
400
700
350
300
500
250
200
2000
2002
2004
2006
2008
2010
2012
2014
2004
2006
Estonia
Estonia
Latvia
Latvia
Lithuania
Sources: Eurostat and Bank of Lithuania calculations.
2008
2010
2012
2014
Lithuania
Sources: Eurostat and Bank of Lithuania calculations.
The structure of households’ disposable income in the Baltic countries from 2012 to 2014 is presented in Chart C. As
shown in the Chart, the share of the compensation paid to employees in Lithuania (62.4%) is significantly lower compared
11
to the share in Latvia (73.5%) or Estonia (86.7%); yet, households’ capital income in Lithuania accounts for a substantially higher share (38.2%) of disposable income (in Latvia and Estonia, they make up respectively 27.7 and 21.4%).
These structure differences can be partly explained by different systems of income taxation and social contributions. For
instance, income taxes and social contributions in Lithuania make up 24.5 per cent of disposable income, of which
income taxes account for 5.7 per cent and social contributions — for 18.8 per cent. In Estonia, income taxes and social
contributions make up 34.6 per cent of disposable income — income taxes make up 10.5 per cent and social contributions — 24.1 per cent. In Latvia, income taxes and social contributions account for one fourth of disposable income,
similar to Lithuania, though their structure is slightly different: in Latvia, income taxes make up 10.5 per cent and social
contributions — 15.4 per cent.
_________________________________
9
In this Annex, to compare country data, the average compensation per employee is defined as the ratio of two national account variables — compensation of
employees and the number of the employees.
For more details about sources of households’ disposable income, see the Lithuanian Economic Review of December 2014.
11
In this Annex, capital income is defined as the sum of property income, mixed income and operating surplus.
10
LITHUANIAN ECONOMIC REVIEW / June 2016
300
28
Chart C. Structure of household disposable income in the Baltic countries
(2012–2014 average, at current prices)
Chart D. Effective tax rates of households’ labour and capital income in
the Baltic countries
(in 2012)
Per cent
140
Per cent
120
35
40
100
35.0
33.0
31.9
30
80
25
60
20
40
15
20
8.2
10
0
4.2
3.0
5
–20
0
–40
Lithuania
Latvia
Labour ITR
Estonia
Compensation of employees
Capital ITR
Labour ITR
Capital ITR
Labour ITR
Estonia
Latvia
Lithuania
Capital ITR
Property income, mixed income and operating surplus
Source: Eurostat.
Social benefits and net other current transfers
Social contributions
Current taxes on income, wealth, etc.
Sources: Eurostat and Bank of Lithuania calculations.
To evaluate the structure of disposable income, which is not distorted by the taxation level, paid taxes and social contributions have to be subtracted from household income. Such estimates are possible by applying the implicit tax rate (ITR). It
shows the actual amount of taxes and social contributions paid by agents of the economy on their income.
2. Disposable income and implicit tax rates
12
When assessing households’ income, two ITRs are calculated — one for labour income and one for capital income.
The ITR on labour income is the ratio of the sum of all direct and indirect taxes and social contributions paid by employees
and employers on employed labour to compensation of employees. This ITR should be viewed as an approximate tax
burden on households’ labour income. The capital ITR is also the ratio of two sums, namely the sum of all direct and
indirect taxes and social contributions paid on property income, mixed income and operating surplus, and the sum of
property income, mixed income and operating surplus. This ITR should be treated as an approximate tax burden on households’ capital income. Chart D shows the ITR of labour income and the ITR of capital income in all three Baltic countries in
2012. As shown in the Chart, Lithuania’s ITR on labour income stood at 31.9 per cent and was the lowest among the Baltic
countries: it was 33.0 per cent in Latvia and 35.0 per cent in Estonia. The situation is different in taxation of households’
capital income which was the highest in Lithuania in 2012. Lithuania’s ITR on household capital income accounted for 8.2
per cent and was almost two times higher than in Estonia (4.2%) and three times higher than in Latvia (3.0%).
Per cent
100
90
80
70
LITHUANIAN ECONOMIC REVIEW / June 2016
60
50
40
30
20
10
0
Lithuania
Latvia
Compensation of employees
Property income, mixed income and operating surplus
Social benefits and net other current transfers
Sources: Eurostat and Bank of Lithuania calculations.
Estonia
Chart F. Relationship between taxation of household income and
disposable income structure in EU countries
(in 2012, at current prices)
Difference between labour and capital shares in disposable income
Chart E. Structure of household disposable income in the Baltic countries,
excluding taxes and social contributions
(2012–2014 average, at current prices)
50
40
Estonia
30
Latvia
20
10
0
Lithuania
–10
–20
–30
–10
0
10
20
30
40
50
Difference between labour income ITR and capital income ITR
Sources: Eurostat, Statistics Lithuania and Bank of Lithuania calculations.
_________________________________
12
The methodology for calculating ITRs for labour and capital incomes and their precise definitions can be found in the Eurostat’s annual publication “Taxation
Trends in the European Union”:
http://ec.europa.eu/taxation_customs/resources/documents/taxation/gen_info/economic_analysis/tax_structures/2014/methodology.pdf.
Chart E shows the structure of household disposable income adjusted for ITR. There are no significant differences
compared to that in Chart C. In Lithuania, compensation of employees accounts for the lowest share of disposable
income, while the share of capital income is the highest among the Baltic countries. It should be noted that due to markedly higher taxes on labour income, compared to capital income, in all three Baltic States compensation of employees
less taxes and social contributions makes up a lower share of disposable income than compensation of employees
including taxes and social contributions: these shares make up respectively 41 and 62.4 per cent in Lithuania, 48.3 and
73.5 per cent in Latvia, and 53.0 and 86.7 per cent in Estonia. Amid low ITR, Baltic countries’ shares of household capital
income excluding taxes and social contributions do not differ substantially from those including taxes and social contributions.
29
It is interesting to analyse the relationship between taxes on household labour and capital incomes and the structure of
13
disposable income of households. Data for EU countries presented in Chart F reveals that there is quite clear connection (negative correlation) between relative labour and capital income taxation and relative labour and capital shares in
disposable income, excluding taxes and social contributions, i.e. the decrease of relative taxation implies the increase of
relative labour and capital shares in disposable income. In addition, the linear relationship shown in Chart shows that if
labour and capital income taxation were equal, labour income would account for about two-thirds, while capital income a
third of disposable income, excluding social benefits and net current transfers.
3.
14
Compensation for labour and labour productivity
According to economic theory, the size of wage depends on labour productivity. This link is the result of the behaviour
of profit maximising companies: companies earn highest profits when wages correspond to the marginal productivity of
labour. In the absence of such correspondence, companies will have incentives to reconsider the number of employees
so that wages would match again the productivity of labour and maximise their profits. If wages are lower than labour
productivity, companies would be tempted to hire more employees. This could boost the demand for labour and build
pressure on wage increase, while declining marginal income would have a negative impact on labour productivity. On the
contrary, if wages are higher than labour productivity, companies would be tempted to reduce the number of employees.
This would have a negative effect on wages and a positive impact on the productivity of labour.
Chart G shows the relationship between hourly labour productivity and hourly compensation of employees in EU
countries. The Chart reveals that the ratio of hourly labour productivity to hourly compensation of employees in the Baltic
countries is broadly in line with this correlation. One should note that, in 2014, labour productivity in Lithuania was higher
than in Latvia and Estonia. As seen from Chart H, labour productivity in Lithuania has been no lower than that in other
Baltic countries for some time already. Differences in Lithuania’s and Latvia’s labour productivity during the entire period
under review remains rather substantial, while Estonia’s labour productivity is quite close to Lithuania’s indicator.
Chart H. Differences in labour productivity across the Baltic countries
(at current prices, in PPP terms)
Per cent
30
12
8
25
4
0
20
–4
–8
15
–12
–16
10
–20
2000
5
20
30
40
50
60
70
Estonia
Latvia
Lithuania
2004
2006
2008
2010
2012
2014
Difference between Estonia's and Lithuania's labour productivity
80
Difference between Latvia's and Lithuania's labour productivity
Labour productivity
EU countries
2002
Sources: OECD and Bank of Lithuania calculations.
Sources: OECD, Eurostat and Bank of Lithuania calculations.
Labour productivity and hourly compensation of employees presented in Chart G and Chart H are adjusted for the
PPP, since differences in currency and price level of different countries would be ignored, if they were calculated at
_________________________________
13
14
Luxembourg, Malta and Portugal are omitted due to a lack of data.
In this Annex, labour productivity is calculated as the ratio of real GDP to hours worked.
LITHUANIAN ECONOMIC REVIEW / June 2016
Hourly compensation of employees
Chart G. Relationship between labour productivity and hourly compensation of employees in EU countries
(in 2014, at current prices, in PPP terms)
30
current or constant prices. The PPP serves two main functions: first, national currencies are converted into one selected
currency; second, countries’ purchasing power is equalised by excluding countries’ price level differences. It means that the
comparison of indicators of various countries, which are calculated adjusted for PPP, reveals only real (quantitative) differences. This is quite important, since the analysis of the price level in the Baltic countries suggests that prices of nearly all
major groups of goods and services in Lithuania are lower than those in Estonia and Latvia (see Chart I).
Chart I. Price level differences in the Baltic countries
(2014)
Per cent, Lithuania = 100
150
145
140
135
130
125
120
115
110
105
100
Latvia
Miscellaneous goods and services
Restaurants and hotels
Education
Recreation and culture
Communication
Transport
Health
Household furnishings, equipment and
maintenance
Housing, water, electricity, gas and other fuels
Sources: Eurostat and Bank of Lithuania calculations.
Clothing and footwear
Alcoholic beverages, tobacco and
narcotics
Food and non-alcoholic beverages
Household final consumption expenditure
95
Estonia
LITHUANIAN ECONOMIC REVIEW / June 2016
The smallest price level differences were found among prices for goods and services produced by the tradable sector,
such as clothes and footwear, fuel, furnishings, household appliances, food, and beverages. Price differences of these
goods and services make up about 0 to 15 per cent. Far higher differences emerge between prices for goods and services
produced by the non-tradable sector, with prices for some goods and services, such as healthcare, education or those
related to housing services, being up to 45 per cent lower in Lithuania than in Latvia or Estonia.
ANNEX 3. Impact of labour market reforms on Lithuania’s economy
31
Introduction
A flexible and effective labour market is one of the major preconditions for sustainable economic development, particularly when a country’s participation in the economic and monetary union is a barrier for a fast adjustment of its economy
to macroeconomic shocks (since a single monetary policy for all countries cannot take into account economic problems
15
specific to each individual country). Under such circumstances, structural reforms become one of the most important
policy measures that help the economy remain competitive, flexible and capable to adapt fast to the global economic
environment. This Annex focuses on the labour market that is of vital importance to both consumers (income related to
employment relationships account for the major share of disposable income) and businesses (their operating results
largely depend on the labour force, one of the major production factors). No wonder that the labour market has an impact
on the goods and services market, prices, competitiveness, life standard, etc.
The Annex focuses on two labour market institutions that have been broadly analysed in economic literature, namely
active labour market policies (ALMPs) and unemployment benefits. The magnitude of the latter is usually estimated by
employing the so-called replacement rate, which measures the share of the previously earned wage, which an individual
who lost his job can expect to receive. Before introducing the results of the analysis that show the impact of these
measures on Lithuania’s economy and establishing their link to the new social model in Lithuania, some insights into the
effects of such measures, which can be found in economic theory and empirical literature, are presented.
1.
Transmission channels of the impact of labour market institutions on the economy
As the economic impact of labour market policies manifests in various ways, first it would be useful to discuss what
the impact is in a closed economy, i.e. to abstract away from the impact related to international trade and the international
16
capital market. Higher unemployment benefits in a closed economy help improve job seekers’ expectations about
compensation as well as increase the employees’ bargaining power, thus leading to the growth of wages and a decrease
in the labour supply. By the way, benefits can also encourage participation in the labour market, as the right to receive
them is acquired only through employment relationships. In such case, the labour supply increases. Finally, since tax
revenues are used to cover benefits, an increase in the tax rate bears negative effects on economic activity.
Empirical studies, such as a research based on the data from 20 OECD countries (Layard et al., 1991), reveals that
the increase in replacement rates leads to the growth of unemployment. The increasing unemployment benefit duration
rather than its amount has the strongest impact on the unemployment rate (Boeri, van Ours, 2008). Consequently,
positive aspects of unemployment benefits (higher financial security, lower risks of changes in income, improved possibilities of preserving human capital amid decreasing pressure to take the first job offered) should not to be assessed separately; on the contrary, they should be assesed together with negative effects — a longer duration of the unemployment
status, lower intensity of job search, higher wage pressures, sustainability of financing resources, and the potentially
sluggish labour market.
Empirical studies have failed to determine any robust impact of ALMPs. For example, when analysing unemployment
dynamics in the OECD countries and the impact of labour market measures (Bassanini and Duval, 2006), it was concluded that unemployment benefits contribute to the increase in unemployment; however, the effects of ALMPs are not clearcut. The research suggests that some types of ALMPs, such as labour market training, have stronger effects on the
decrease in unemployment. Heckman et al. (1999) determined that ALMPs bear different effects on different employees’
groups, yet the effects of ALMPs on employment prospects are modest. Research based on micro-level data reveal a
positive effect, linked to activation measures (Boeri, van Ours, 2008), yet the results of micro-level data-based research
17
are usually rather obscure.
However, all the above-mentioned papers fail to recognise one significant aspect — the importance of a country’s
economic openness. The impact of labour market institutions depends on the level of economic openness, while economic openness can have important implications for the functioning of the labour market as well.
_________________________________
15
It is applicable also when speaking about the period, when Lithuania’s monetary system was based on the currency board arrangement, and the litas was
pegged to the US dollar, and later — to the euro.
16
It is assumed that the country is an autarky, i.e. it does not trade with other countries.
17
Possible explanations include the following: a crowding-out effect (one employment programme participant that got a job reduces job finding odds for a nonprogramme participant), programme participant’s decreased job search intensity, fiscal replacement effect (when a positive impact of ALMPs is basically offset
by a negative impact related to a tax increase linked to the financing of the programme), etc.
LITHUANIAN ECONOMIC REVIEW / June 2016
Another labour market institution, ALMPs, is divided into training, employment subsidies, public work programmes,
and activation, i.e. increasing incentives for participation in the labour market. The positive aspects of ALMPs are obvious: improvement and acquisition of skills demanded by the labour market, lower uncertainty regarding the employee’s
suitability, etc. The use of ALMPs is often a precondition for receiving an unemployment benefit. This is where the negative impact kicks in, i.e. job search intensity may decrease when participating in a public employment programme.
2. Economic theory insights into the structural labour market measures of an open economy
32
Economists agree about the necessity of well functioning labour market institutions, but, as Blanchard (2006) accurately
summarises, one thing is to know that they matter, and quite the other is to know exactly which ones matter and in what
way. A conceptual understanding of the impact of labour market measures is necessary to assess the importance of
structural reforms for the economy. Since Lithuania’s economy is small and very open, this section discusses theoretical
models of an open economy, namely insights from theoretical research on the impact of international trade on the labour
market and the impact of the labour market on economic openness.
Felbermayer et al. (2011) state that, under certain assumptions, labour market tightness and the number of producers of
intermediate goods do not have any effects on labour productivity, and, therefore, economic policy should be primarily used
to reduce barriers to market entry and promote international trade. According to Dutta et al. (2009), even though the impact
of international trade on the labour market largely depends on the nature of trade (i.e. on factors determining country’s
competitive advantage), in the long-run, trade liberalisation is related to lower unemployment rates. Other theoretical
studies reveal that the relation between economic openness and the labour market may be far more nuanced. For instance,
the work by Helpman and Itskhoki (2010) suggests that trade liberalisation may lead to lower unemployment, provided that
the labour market in trading sectors is more flexible than in non-trading ones, and to higher unemployment, if the labour
market in non-tradable sectors is more flexible. In a subsequent paper (Itskhoki and Helpman, 2015), authors emphasise
that even though higher economic openness is often accompanied by employees’ lay-offs and bankruptcies of the least
productive enterprises, the negative effect is offset by the performance of the most-productive exporters. Another important
finding of this research is that, with more intense international trade, adjustment costs are lower when the labour market is
more flexible. Consequently, changes in the labour market, which help boost its flexibility, may speed up the adjustment to
a more interconnected economic environment.
The question may also be analysed from another perspective, i.e. by looking at the impact of the labour market on the
country’s economic openness. For example, Felbermayer et al. (2013) emphasise that labour market institutions have an
impact on terms of trade and, consequently, on trade itself. Thus, when considering labour market reforms, the impact on
relative terms of trade should also be taken into account, as the terms of trade may prompt changes in the country’s specialisation and the structure of the export sector.
Lastauskas and Stakėnas (2015) also analyse the effects of labour market institutions on the country’s economic openness, yet, the economy in their model has a more complicated (sectoral) structure compared with the one in the study by
18
Felbermayer et al. (2013). According to their model, labour market measures induce changes to labour market tightness
which, in turn, affects wages and prices. However, the impact on economic indicators depends on whether the market of
homogenous economic goods is capable of absorbing the impact of labour market changes. The model was used for the
19
empirical analysis of 15 European countries ; it showed that changes in labour market institutions would have heterogeneous effects on economies in the analysed sample. However, if labour market reforms were implemented simultaneously in
all countries, their effects would be much more aligned, due to spillover effects that compensate each other.
Felbermayr et al. (2015) underline the role of spillover effects in another paper as well. The model demonstrates that
unemployment benefits increase unemployment not only in the country undergoing a reform, but also in all its trading
partners. It is important to note, however, that in order to make the effect close to its empirical counterparts, wages need to
be quite rigid. However, theoretical literature increasingly comes to a conclusion that the impact of labour market measures
should not be analysed separately, without linking it with countries with which the country undergoing a reform has economic ties.
LITHUANIAN ECONOMIC REVIEW / June 2016
3. Replacement rates and the impact of active labour market policies on Lithuania’s economy
This section reviews empirical results from a study that models Lithuania’s economy as part of the global trade network.
The aim of the research was to find out the effects of the change in some labour market policies on Lithuania’s economy.
The impact was estimated both domestically and globally.
The empirical model is based on theoretical literature, suggesting that labour market policies affect labour market tightness, whilst the latter affects unemployment. As unemployment has an impact on income, prices, competitiveness, and
economic openness, all these variables must respond to changes in unemployment. Taking this into consideration, the
empirical macroeconomic model is built using real GDP, unemployment, the level of openness to international trade (inter20
national trade over GDP), and the real effective exchange rate. Two institutional variables that characterise the labour
market are also included: unemployment benefits (replacement rate) and expenditure on ALMP over GDP.
To find out whether Lithuania’s (the economy of which is rather small) economic openness and integration into the global trade network may have effects on the efficacy of labour market reforms, three vector autoregression models have been
estimated: 1) a basic model, which does not include variables characterisingeconomies of Lithuania’s trade partners; 2) a
_________________________________
18
Unlike in the model by Felbermayer et al. (2013), their economy consists of two sectors — differentiated and homogeneous goods.
The GVAR methodology applied in the empirical part of the research, inter alia, makes it possible to take into account economic interlinkages among countries.
20
It is defined as a ratio of the domestic labour price to a weighted average of labour prices in trading partners.
19
model, which includes the above-mentioned variables, but does not account for feedback effects (variables characterising
the economies of Lithuania’s trading partners may affect Lithuanian economic variables but not vice versa); 3) a model
21
that also allows for feedback effects. The results are summarised by discussing the impact of the replacement rate and
expenditure on ALMP on GDP, the unemployment rate, economic openness, and the real effective exchange rate.
33
Chart A and Chart B show the impact that the unemployment replacement rate and expenditure on ALMP have on
GDP. Excluding the impact of foreign markets, it may seem that higher unemployment benefits contribute to an increase
in GDP, while expenditure on ALMP contributes to a decrease in GDP. However, the total foreign market impact outweighs the direct effects. The overall result is that unemployment benefits have almost no effect (or a slightly negative
effect) on GDP, while the influence of changes in expenditure on ALMP is substantially positive. When estimating the
shock caused by expenditure on ALMP, it was determined that a 1 per cent increase in such expenditure raises GDP by
0.035 per cent in two years after the shock. Though the impact on GDP exerted by the expenditure on ALMP may look
insignificant, it should to be evaluated taking into account the overall context: in 2013, expenditure on ALMP accounted
for only 0.23 per cent of GDP; consequently, its increase by 1 per cent cannot cause a strong response in GDP. With
regard to proposals concerning the new social model in Lithuania, expenditure on ALMP is likely to grow approximately
by 25.5 per cent. If this turns out to be true, two years after changes in the expenditure on ALMP, the response in GDP
would account for 0.89 per cent.
Chart A. Change in GDP due to 1 per cent increase in the unemployment
replacement rate
Chart B. Change in GDP due to 1 per cent increase in expenditure on
active labour market measures
Per cent
Per cent
0.40
0.04
0.35
0.03
0.30
0.25
0.02
0.20
0.01
0.15
0.10
0
0.05
0
–0.01
–0.05
–0.02
–0.10
0
4
8
12
16
20
24
Model without foreign variables
Model without feedback effects from abroad
Model with feedback effects from abroad
28
0
32
36
40
Quarter after shock
4
8
12
16
20
24
Model without foreign variables
Model without feedback effects from abroad
Model with feedback effects from abroad
28
32
36
40
Quarter after shock
Source: Bank of Lithuania calculations.
Source: Bank of Lithuania calculations.
The effects of the replacement rate and expenditure on ALMP on the unemployment rate (see Charts C and D) basically replicate insights about the impact on GDP. The unemployment rate, excluding the impact of foreign variables, may
go down due to an increase in unemployment benefits and remain broadly unchanged due to the changes in expenditure
on ALMP. However, when simulating the impact of labour market changes on foreign markets and aggregate impact of
spillover effects on Lithuania’s labour market, a literature-proven effect is determined: by affecting job seekers’ motivation
and boosting additional financing burden, a higher unemployment replacement rate increases unemployment, while
surging expenditure on ALMP decreases unemployment.
Chart C. Change in the unemployement rate due to 1 per cent increase
in the unemployment replacement rate
Chart D. Change in the unemployment rate due to 1 per cent increase in
expenditure on active labour market measures
1.0
0.2
0.5
0.1
0
0
–0.1
–0.5
–0.2
–1.0
–0.3
–1.5
–0.4
–2.0
–0.5
–2.5
–0.6
–0.7
–3.0
0
4
8
12
16
20
24
Model without foreign variables
Model without feedback effects from abroad
Model with feedback effects from abroad
28
32
40
Quarter after shock
Source: Bank of Lithuania calculations.
_________________________________
21
36
For more details, see Lastauskas and Stakėnas (2016).
0
4
8
12
16
20
24
Model without foreign variables
Model without feedback effects from abroad
Model with feedback effects from abroad
Source: Bank of Lithuania calculations.
28
32
36
40
Quarter after shock
LITHUANIAN ECONOMIC REVIEW / June 2016
Per cent
Per cent
Impact on economic openness and competitiveness is summarised in Charts E, F, G and H. Economic openness (the
ratio of the sum of export and import to GDP) increase is fuelled by unemployment benefits and decrease is driven by
changes in expenditure on ALMP. This change can be explained by two aspects: unemployment benefits decrease GDP
and, at the beginning, have a negative effect on competitiveness (see Chart E); ALMPs, on the contrary, firstly increase
GDP and improve competitiveness of labour costs of Lithuanian exporters compared to other trading partners, but later
decrease it (the result is similar to the J-curve effect, when the initial effect is later overridden by changes in the economic
conditions). Spillover effects are very important for economic openness because of the impact on trade terms (the ratio of
export and import prices), as the latter may be critical for the final effect of the labour market reform.
34
Chart E. Change in openness due to 1 per cent increase in the unemployment replacement rate
Chart F. Change in openness due to 1 per cent increase in expenditure
on active labour market measures
Per cent
Per cent
0.20
0.02
0
0.15
–0.02
0.10
–0.04
0.05
–0.06
0
–0.08
–0.05
–0.10
–0.10
–0.12
–0.15
–0.14
–0.16
–0.20
0
4
8
12
16
20
24
Model without foreign variables
Model without feedback effects from abroad
Model with feedback effects from abroad
28
0
32
36
40
Quarter after shock
4
8
12
16
20
24
Model without foreign variables
Model without feedback effects from abroad
Model with feedback effects from abroad
28
32
36
40
Quarter after shock
Source: Bank of Lithuania calculations.
Source: Bank of Lithuania calculations.
Interpreting changes in economic openness of a country, presented in Charts E and F, may be difficult not only because
this variable depends on changes in the comparative basis (GDP), but also because it is impossible to determine the
dynamics ofthe number of trading partners of all enterprises in the country (the so-called extensive margin of trade). To
estimate this aspect, a satellite model is built, which shows that, among modelled macroeconomic variables, GDP is the
22
biggest contributor to changes in the extensive trade margin. So, an increase in unemployment benefits, decrease GDP
and consequently lead to a decline in the number of trading partners of different Lithuania’s economic sectors. As intermediate goods used in production account for a large share of the Lithuanian trade, this should be a strong argument for
unemployment benefits not to be increased unduly.
Chart G. Change in the real effective exchange rate due to 1 per cent
increase in the unemployment replacement rate
Chart H. Change in the real effective exchange rate due to 1 per cent
increase in expenditure on active labour market measures
Per cent
Per cent
0.35
0.05
0.30
0.04
0.25
0.03
0.20
0.15
0.02
0.10
0.01
0.05
0
0
–0.01
LITHUANIAN ECONOMIC REVIEW / June 2016
–0.05
–0.02
–0.10
0
4
8
12
16
20
24
Model without foreign variables
Model without feedback effects from abroad
Model with feedback effects from abroad
Source: Bank of Lithuania calculations.
28
32
36
40
Quarter after shock
0
4
8
12
16
20
24
Model without foreign variables
Model without feedback effects from abroad
Model with feedback effects from abroad
28
32
36
40
Quarter after shock
Source: Bank of Lithuania calculations.
4. Changes in unemployment benefits and expenditure on ALMP foreseen in Lithuania’s social model
The insights presented by the model that also allows assessing foreign markets’ feedback effects may be used to estimate plausible effects of some of the components of the new social model in Lithuania on the country’s economy. Out of
the planned labour market reform, only the effects of the described labour market measures have been chosen for the
analysis. A significant portion of the planned reform under the social model is difficult to quantify (such as the diversity of
employment contract types, flexibility, bargaining power, etc.), therefore, this model cannot be used to estimate its impact. It
_________________________________
22
In this case, an extensive trade margin was defined by using intersectoral data, i.e. it shows changes in the number of economic sectors of foreign countries,
which trade with Lithuanian enterprises. For more information about the satellite model, see the article by Lastauskas and Stakėnas (2016).
is obvious that assumptions and limitations of the model
have to be taken into account to assess the results (other
factors are deemed unaffected by changes in ALMPs and
unemployment benefits).
Chart I. Dynamics of the unemployment replacement rate by benefit
payout month
Per cent
80
35
70
When estimating potential replacement rate changes, a
comparison is made between effective procedures for
50
awarding unemployment benefits and procedures proposed in the draft law on the new social model in Lithua40
23
nia . The data by the Board of Social Insurance Fund
30
(Sodra) of February 2016 on insured income is used, as
20
well as data on the minimum monthly wage, state10
supported income, insured income, and average wage in
0
2016. The results received are presented in Chart I: after
1
2
3
4
5
6
7
8
9
Month of unemployment
Effective law
the new procedure is implemented, the largest changes in
Proposed law
the amount of benefits would be seen starting with the sixth
Source: Bank of Lithuania calculations.
month of unemployment. The change would be rather
pronounced; moreover, a long duration of the unemployment benefit is an important factor governing the unemployment rate. Obviously, when estimating the magnitude and duration effects of unemployment benefits on the economy, business cycle duration and public finance sustainability also have to be taken into account.
60
Chart J shows unemployment benefit amounts in absolute terms based on effective and proposed procedures. It is
assumed that the work experience of an employee does not exceed 25 years. In addition, an income tax on unemployment benefits proposed in Annex III-6 of the report on Lithuania’s social model has been employed, which is not provided
for under the currently effective procedures. Similarly as in the case of the replacement rate, the largest gap between
unemployment benefits under the effective and proposed procedures is seen starting with the sixth month of unemployment. Consequently, the motivation to search for a job would decrease not only for individuals with low, but also with
average past income (due to a too strong response of the unemployment benefit to the income during the late phase of
the unemployment period). Another problem that may arise due to the labour market reform model is the elimination of
the employment experience importance for the unemployment duration. The underlying assumption seems to be that
individuals with a long employment history, and hence older unemployed, have the same opportunities to find a job as the
24
younger ones. There is no empirical proof for such an assumption. Moreover, long unemployment benefit duration
reduces job search motivation for younger individuals who have better chances of adapting to the labour market and
25
changing their job profile, and increases their willingness to work illegally.
Chart J. Unemployment benefits depending on unemployment duration and the amount of insured income received
1–3 months of unemployment
Benefit in euro
600
4–6 months of unemployment
Benefit in euro
7–9 months of unemployment
600
500
500
500
400
400
400
300
300
300
200
200
200
100
100
100
0
0
0
350
550
750
950
Proposed law
Effective law
Source: Bank of Lithuania calculations.
1150
1350
Insured income in euro
350
550
750
950
Proposed law
Effective law
Source: Bank of Lithuania calculations.
1150
1350
Insured income in euro
350
550
750
950
Proposed law
1150
1350
1550
Insured income in euro
Effective law
Source: Bank of Lithuania calculations.
Changes in expenditure on ALMP were estimated based on a proposal to impose a 15 per cent income tax on unemployment benefits and use the revenues received to finance ALMPs. It is assumed that this would be an additional
financing source for ALMPs. It is estimated that, with the said procedures in place, the expenditure on ALMP would have
been higher by 25.5 per cent on average in 2010–2013. After applying the defined changes to labour market variables,
responses of macroeconomic variables are determined (see Chart K). A model, which integrates the impact of Lithuanian
economy on foreign economic variablesalong with the feedback effect, is used for estimation.
_________________________________
23
The draft law is available at http://www.socmodelis.lt.
Hall and Schulhofer-Wohl (2015) revealed that differences among job seekers determine different job finding probabilities. If we assume that chances of
finding a job are equal, empirical results will not be reliable. Neumark et al. (2015) have empirically confirmed that finding a job is far more difficult for older
women; discrimination against men on the grounds of age is less common.
25
Hartz reforms were implemented in Germany based on similar arguments. Well before the global financial crisis the reforms substantially reduced the
unemployment benefits for long-term unemployed. In economic literature, Hartz reforms are often seen as one of the major factors that boosted Germany’s
resilience to the crisis, see Krebs and Scheffel (2013).
24
LITHUANIAN ECONOMIC REVIEW / June 2016
Benefit in euro
600
36
The results show that, in an approximately two-year period, changes in unemployment benefits and expenditure on
26
ALMP would raise the unemployment rate by 15 per cent and make the GDP shrink by about 0.5 per cent. In the longer
run, the impact on unemployment would decline to around 10 per cent, while GDP may remain unaffected. Both elements
of the reform have a positive effect on economic openness and competitiveness (of prices): the ratio of external trade
volumes to GDP increases by 2 per cent, while real effective exchange rate decreases by about 0.5 per cent. All these
results depend largely on the impact of unemployment benefits. Obviously, the total impact of the reform eventually depends on specific parameters of both reforms: in lowering the amount (or duration) of unemployment benefits or increasing
expenditure on ALMP, negative effects on GDP and unemployment could be mitigated or even eliminated.
Chart K.Changes in macroeconomic variables due to changes in expenditure on active labour market measures and the unemployment replacement rate,
estimated based on proposals of the new social model
Per cent
Per cent
Unemployment rate
35
GDP
1.5
30
1.0
25
20
0.5
15
10
0
5
–0.5
0
–1.0
–5
–10
–1.5
–15
–20
–2.0
0
4
8
12
16
20
24
28
Change due to ALMP
Change due to replacement rate
Total change
32
36
40
Quarter after shock
Source: Bank of Lithuania calculations.
Per cent
0
4
8
12
16
20
24
28
Change due to ALMP
Change due to replacement rate
Total change
32
36
40
Quarter after shock
Source: Bank of Lithuania calculations.
Per cent
Real effective exchange rate
1.5
8
1.0
6
0.5
Economic openness
4
0
2
–0.5
0
–1.0
–2
–1.5
–2.0
–4
0
4
8
12
16
Change due to ALMP
Change due to replacement rate
Total change
Source: Bank of Lithuania calculations.
20
24
28
32
36
40
Quarter after shock
0
4
8
12
16
Change due to ALMP
Change due to replacement rate
Total change
20
24
28
32
36
40
Quarter after shock
Source: Bank of Lithuania calculations.
LITHUANIAN ECONOMIC REVIEW / June 2016
Conclusions
Even though unemployment benefits help to reduce the income loss risk and increase financial security for the unemployed (an individual has more time to search for a job that better suits his/her skills), the negative influence of their change
on income, unemployment rates and competitiveness should be taken into account as well. International trade only
strengthens negative effects of changes in unemployment benefits; attention should be paid not only to the change in the
amount of unemployment benefits, but also to the change in duration. A large increase in unemployment benefits may
contribute to a long-term structural unemployment. A proposal not to link the benefit payout duration to employment history
will hardly encourage young jobless individuals to search for a job more intensively. Moreover, an increase of the benefits to
long-term job searchers not only would reduce competitiveness and increase unemployment, but also would have an
opposite effect compared to the results of Hartz reforms that helped the German economy remain competitive.
One of the major conclusions of this analysis is that competitiveness at international level cannot be dismissed, particularly when analysing Lithuania’s economy, the openness of which is above 50 per cent. Labour market reforms affect
trading partners and these effects may potentially come back to Lithuania. A too high unemployment replacement rate may
have a negative effect on competitiveness and increase economic opnennes due to a decline in GDP. Extensive margin of
trade is likely to drop due to unemployment benefits. On the contrary, active labour market measures have a positive effect
on both competitiveness and Lithuania’s major trading partners. Thus, shorter duration of unemployment benefits, combined with more effective training for the unemployed people and improved activation policy, could lead to desirable macroeconomic results.
_________________________________
26
Based on Eurostat data, the unemployment rate in Lithuania in 2016 was 8.8 per cent. Consequently, a 15 per cent increase could raise it to 10.12 per cent.
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