Publications

In 2021, the Bank of Lithuania and the Competition Council published a study assessing the accessibility of financing sources for small and medium-sized businesses (SMEs) in Lithuania in 2018–2019 and the factors limiting it. The study results have revealed that the funding opportunities for SMEs in Lithuania could be limited by various long-term constraints, including the lack of the enterprises’ adequate collateral and a higher risk of some enterprise groups, which has not always received due consideration through state aid measures.

In order to obtain sufficient funding, SMEs are faced with the collateral requirements which are often more difficult to comply with due to the inadequate assets in their possession. One of the measures that allows addressing the problem of inadequate assets of SMEs is loan guarantees. With this measure, the guarantor assumes part of the credit risk, which makes it possible to mitigate the risk for the credit institution and to enable SMEs to obtain adequate funding. However, in the previous study of the Bank of Lithuania and the Competition Council, which analysed SMEs’ access to the funding sources in 2018-2019, the results of the econometric modelling applied did not indicate any significant impact of state guarantees on the size of collateral requested by lenders.

This study is aimed at reviewing in greater detail the international practice of applying state guarantees (Section1) and Lithuania’s experience (Section 2), and at assessing the effectiveness of guarantee instruments in Lithuania, taking into account the groups of enterprises that received a guarantee and the effect of guarantees on the terms of lending (Section 3). In light of the results, lines of action to contribute to the development of these measures are proposed (Section 4).

Keywords: State guarantees, small and medium-sized businesses, access to finance, collateral requirements

The views expressed are those of the author(s) and do not necessarily represent those of the Bank of Lithuania.

Available only in Lithuanian

After a decade of muted consumer price growth, inflation has picked up again, with the price increase of many goods and services spiking in 2022. Two extraordinary events – the COVID-19 pandemic and the Russian aggression against Ukraine – played a leading role in the jump in inflation. The high risk of deep recession in 2020-2021 forced governments and central banks to implement various supportive measures. As the economies adapted to the pandemic, recoveries followed unexpectedly quickly with the help of expansive monetary and fiscal policies. Nevertheless, pandemic-induced supply-chain disruptions have resulted in delivery delays and increased production and transportation costs across the globe. Thus, recovering demand faced a still-constrained supply. In 2021, recovering economies were hit by another shock – the Russian war against Ukraine. The war contributed to a rise in energy prices (notably, that of natural gas, which Europe was especially dependent on). All these factors – expansionary fiscal and monetary policies, rapidly recovering economies, residual post-pandemic disruptions in supply chains, and increases in energy prices – have led to an unexpected rise in inflation throughout the world, including Lithuania.

In this occasional paper, we analyse various topics related to inflation in Lithuania, predominantly focusing on the recent inflationary episode. The latter rise of inflation was unprecedented. In 2022, average annual inflation reached 18.9 per cent in Lithuania, a level which had not been seen for more than two decades. We analyse the nature of the recent inflation shock, duration, underlying causes, and consequences. While this study mainly deals with Lithuania, it also addresses the question of whether its inflation dynamics differs from that in the rest of the euro area, and if so, how. The study thus contributes to a more nuanced understanding of inflationary process in Lithuania. While integrated within the general topic, each of the chapters in the study can be seen as separate analytical notes focusing on distinct topics.

In Section 1.1. (“Stylized facts of consumer price dynamics”) and Section 1.2 ("Dynamics of consumer, producer and input prices”), we provide an overview of the dynamics of inflation and its components in Lithuania over the past two decades. During the economic boom of 2004 to 2008, Lithuania experienced an upward pressure in consumer prices. This ended in 2009 with the global financial crisis, which triggered a significant downturn in the Lithuanian economy. Afterwards, a period of relative stability in inflation took place until the COVID-19 pandemic. At its start in 2020, consumer price inflation decelerated, but price growth picked up in 2021-2022. Since reaching its peak in 2022, the annual inflation rate has been steadily declining. Historically, energy prices in Lithuania have been characterized by especially high volatility. During periods of higher inflation, they have been one of the main drivers of inflation, while during periods of lower inflation, energy prices have been an important factor reducing it.

In Section 1.3. (“Inflation expectations of Lithuanian households”) and Section 1.4. (“Inflation expectations of Lithuanian firms”), we use existing survey data on Lithuanian households’ and firms’ inflation expectations to better understand their evolution in the recent high inflation environment. A clear upward bias can be observed in households’ and firms’ inflation expectations. However, there is also a significant co-movement between actual inflation and inflation expectations. As inflation started to decline in 2023, similar trends can be observed in inflation expectations. 

In Section 2.1. (“Effects of energy supply shocks on price inflation along the production chain”), we assess the impact of energy supply shocks on price inflation along the production chain in Lithuania. The energy shocks are identified in two independent monthly BVAR models (Messner and Zorner (2023)). Producer price inflation for energy and food reacts at half the rate of equivalent international inflation in the month of the shock and then continues to rise for a year or year and a half. Consumer food price inflation reacts to a similar extent as producer food price inflation, while consumer energy price inflation reacts to a lesser extent than producer energy price inflation. More importantly, these reactions occur with a lag of about one year after the shock. Finally, the impact at the bottom of the production chain, i.e. on core consumer price inflation, is quite limited. Overall, this section shows that energy supply shocks propagate gradually through the supply chain over time and are not passed on, on a one-by-one basis, to the final consumer.

In Section 2.2. (“Wage and price responses to aggregate and labour market shocks”), we assess how global and labour market shocks affect wages and consumer prices in Lithuania, and how wage responses in turn affect prices in a quarterly BVAR. Aggregate demand, aggregate supply, labour supply and wage markup shock s are identified following Foroni et al. (2018). The impulse response functions (IRFs) show that global macroeconomic shocks have a persistently higher impact on wages (hourly earnings) and consumer prices than labour-specific shocks. Typical price and wage reactions have their maximum effects after about a year, underlining their rigidity to change. Counterfactual scenarios, in which wages do not react to shocks, reveal that such wage-price spirals can be significant after aggregate supply and demand shocks. Following a demand shock, wage reactions fuel price reactions in the medium term. Following a supply shock, wage reactions counterbalance price reactions over time.

In Section 2.3. (“Energy price inflation shocks in Lithuania and the Euro area”), we analyse how the energy price shocks affect economies in Lithuania and the Euro area. We estimate two separate BVAR models (one for Lithuania, the other for the EA), including respective time series from 2002Q1 to 2022Q4 of yoy energy, food, and core HICP inflation, as well as the unemployment rate and yoy total compensation per employee, following Corsello and Tagliabracci (2023). The IRFs show that Lithuania was more vulnerable to, and more affected by, energy price inflation shocks than the EA on average over the period. For an equivalent energy shock, the effects on HICP consumer price and wage inflation were larger and more persistent.

In Section 2.4. (“What has driven the surge in inflation in Lithuania? A production-side decomposition.”), using input-output tables, we decompose the inflation into its four drivers – prices of energy, prices of other imported products, wages and gross operating surplus. In our analysis, we focus on the period from 2021Q1 to 2023Q2 and find that all these supply-side factors contributed significantly to the increase in price level. We show that wage increases accounted for 40% of the calculated increase in price level, while the remaining increase was accounted for in broadly similar proportions by higher energy costs, more expensive imports of non-energy goods and services, and an increase in non-energy sector gross operating surplus (profit). The analysis also indicates that the recent increase in production costs has not yet been fully passed on to consumer prices in 2023Q2.

In Section 2.5. (“Lithuania’s nominal effective exchange rate fluctuations and domestic inflation.”), we analyse whether changes in nominal effective exchange rates have played a significant role in the recent surge of inflation. A relatively large share of Lithuanian imports is denominated in foreign currency, implying that inflation can be at least partially explained by currency depreciation. To determine the exchange rate pass-through to prices, a simple VAR analysis is conducted. The results of analysis indicate that exchange rate pass-through to import prices is incomplete in Lithuania, meaning that there is no tit-for-tat increase in import prices following currency depreciation. The pass-through for producer and consumer prices is even lower. Nominal exchange rate developments explain slightly more than 10% of import price variability, yet only about 1% of producer and consumer price variability. It follows that although the depreciation of the euro contributed to increasing inflation in the most recent inflation period (2021–2022) in Lithuania, its impact on producer and consumer prices was very limited.

In Section 2.6 (“A comparison of consumption basket item weights and price levels in Lithuania and the euro area”), we analyse if the differences in the composition of consumption baskets in Lithuania and euro area can explain a significant portion of inflation differentials. While gradually converging, the structure of the Lithuanian consumption basket still differs somewhat from that in the EA average. The greatest differences exist in the weights of services and food. In countries with a higher standard of living, households tend to spend less on basic needs and more on services. The same trends are observed in the development of the Lithuanian economy; as the standard of living approaches the EU average, the price level also converges, and services become a more prominent part of the consumption basket. Different weights of various goods and services in consumption baskets lead to different item weights for inflation calculation. Our calculations show that if in Lithuania we had HICP weights equal to those in the EA, our average annual headline inflation rate would have been about 1.6 percentage points lower than the factual in 2022.

In Section 2.7. (“Can price level convergence explain longer-term differences in inflation rates across euro area countries?”), following Honohan and Lane (2003), we provide evidence that in a monetary union, remaining price level differences lead to higher inflation in countries with lower price levels. For every single percentage point (pp) deviation below the average price level, countries experience around 0.02-0.036 pp higher inflation. In 2022, the price level in Lithuania was still 26 percent below the EU average. This would imply that the annual inflation in Lithuania could be about 0.5-0.9 pp higher than EA average due to the price level convergence in 2022.

The unexpectedly high inflation has affected government finances substantially. In Section 3 (“Implications of temporary acceleration in inflation for public finances”), we analyse the implications of higher inflation on the fiscal position of the general government sector. We break down recent general government revenue growth into four explanatory factors: real economic activity, price growth, the effect of government’s discretionary decisions (fiscal measures) and the unexplained component or tax residual. Our decompositions show that in 2021-2022, the observed increase in tax revenue was significantly affected by the strong growth of the macroeconomic bases and implemented fiscal measures. As regards the impact of inflation, more than half of the increase in receipts from VAT, personal income tax and social contributions can be attributed to the rise in the price component. As inflation decelerates, there will be a corresponding slowdown in the nominal GDP growth and the deceleration in goods and services inflation. This would naturally slow the growth of general government revenue.

All in all, this analysis implies that during the periods of a temporary increase in inflation fiscal policy should resist using the inflation-induced proceeds to finance permanent increases in spending. In the near future, inflation could show persistence and respond more slowly to changing trends in import and producer prices (compared to the upswing) since not all of the increased costs were fully passed through to consumer prices by the middle of 2023. In the longer term, inflation prospects in Lithuania will depend not only on economic policy but also future changes in the energy sector and climate-related developments and their impact, as well as the ability to adapt to those shifts.

Keywords: inflation, convergence, price level, supply shock

JEL Codes: C25, E61, G18, G21, G51

The views expressed are those of the author(s) and do not necessarily represent those of the Bank of Lithuania.

2023 was the first year in which issuers (non-financial companies) were required or voluntarily disclosed, in accordance with the requirements set out in Article 8 of the Taxonomy Regulation, how and to what extent the undertaking’s activities are associated with economic activities that qualify as environmentally sustainable. The Overview of Issuers’ Non-financial Information in Accordance with the Disclosure Requirements of Article 8 of the Taxonomy Regulation prepared by the Bank of Lithuania assesses how issuers applied the requirements for disclosing sustainability indicators, identifies shortcomings and provides recommendations. The overview assesses the non-financial information of 19 issuers (non-financial companies) disclosed in the social responsibility reports and related to the requirements of Article 8 of the Taxonomy Regulation. The recommendations concern the scope and content of the disclosed information, the use of templates for mandatory information disclosure and voluntary sustainability disclosure.

The views expressed are those of the author(s) and do not necessarily represent those of the Bank of Lithuania.

All real economic sectors depend on nature. Accordingly, lending to economic sectors carries some degree of nature-related financial risk. To assess and mitigate the potential impact of ecosystem service loss on financial stability, it is crucial to identify and measure nature-related financial risks. Using FINREP and ENCORE data, we assess the direct material dependence on nature and evaluate physical nature-related financial risks in Lithuanian commercial bank lending. While a substantial share of bank loans (70,1%) in Lithuania goes to sectors that are very highly dependent on at least one ecosystem service, the financial risks arising from hypothetical scenarios of disruption in the provision of some of these ecosystem services is markedly lower than in other European countries due to Lithuania’s geographic specificity. The case study of Lithuania illustrates that the impacts from the loss of ecosystem services are not uniform across geographic regions, that the assumption that the level of dependence on ecosystem services can serve as an approximation of physical nature-related financial risks is inappropriate for certain geographies, and that an accurate assessment of nature-related financial risks requires location-specific dependency-risk mapping matrices.

Keywords: Ecosystem Services, ENCORE, Nature-related Financial Risks, Financial Stability

JEL Codes: 58, G21, Q01, Q57

The views expressed are those of the author(s) and do not necessarily represent those of the Bank of Lithuania.

The need for transparent sustainability financial information has been growing rapidly in recent years. Financial information is no longer sufficient for investors and the public, they are looking at how sustainability-related risks are linked to the business strategy of the financial market participant and integrated into the management of other risks, as well as how sustainability aspects are addressed by the financial market participant. In the context of growing interest of the public and stakeholders in sustainable finance, financial market participants are expected to disclose sustainability information not only in accordance with the binding sustainability disclosure requirements in force, but also to do so voluntarily, clearly and in full detail.

Given the relevance of the topic, the Bank of Lithuania carried out an analysis of sustainability disclosure practices of insurance undertakings and credit institutions, the aim of which is to review the sustainability information disclosed by institutions, its content and scope, and to identify good practices and provide recommendations to market participants.

This overview presents sustainability disclosure practices of insurance undertakings and credit institutions established in Lithuania. The analysis was based on information and data available on websites from 1 July 2022 to 1 November 2022. The overview consists of three parts: the first is aimed at reviewing compliance with the disclosure requirements set out in Articles 3 to 5 of Regulation (EU) 2019/2088 on sustainability-related disclosures in the financial services sector, the second focuses on compliance with the obligation to prepare social responsibility reports laid down in the Republic of Lithuania Law on Financial Reporting by Undertakings, and the third on the state of play of voluntary disclosure of sustainability information. In each part, we present good practice tables that we believe can be useful for improving sustainability disclosure practices.

The following credit institutions established in Lithuania participated in the analysis:

European Merchant Bank UAB, AB Fjord bank, UAB GF bankas, the United Central Credit Union, the Lithuanian Central Credit Union, AB Mano bankas, UAB Medicinos bankas, PayRay Bank, UAB, Revolut Bank UAB, AB SEB bankas, UAB SME Bank, Swedbank, AB, AB Šiaulių bankas (hereinafter – credit institutions),

as well as the following insurance undertakings established in Lithuania:

Allianz Lietuva gyvybės draudimas UAB, Compensa Vienna Insurance Group, ADB, ERGO Life Insurance SE, ADB Gjensidige, UAB draudimo kompanija LAMANTINAS, AB Lietuvos draudimas, UAB PZU Lietuva gyvybės draudimas, Gyvybės draudimo UAB SB draudimas, INVL Life, UADB, (hereinafter – insurance undertakings) (credit institutions and insurance undertakings jointly – financial institutions, financial market participants).

Available only in Lithuanian

The high-paced growth of the Lithuanian mortgage market may cast doubt on either the efficacy of the country’s macroprudential toolkit, or the appropriateness of its current parametrisation in putting a backstop to excessive dynamics. This paper assesses the adequacy of BBM’s in Lithuania by building a novel lifetime expected credit loss framework that is founded on actual loan-level default and household income data. Based on the modelling framework we document seven findings which are relevant for policymakers. We show that the BBM package effectively contains mortgage credit risk and that housing loans are more resilient to stress than in the pre-regulatory era. Our BBM limit calibration exercise reveals that: i) in the low-interest rate environment income-based measures could have been tighter; ii) borrowers taking out secondary mortgages rightly are and should be required to pledge a higher down payment of at least 30%.

Keywords: macroprudential policy, borrower-based measures, LTV, mortgage credit risk, lifetime expected credit loss, probability of default.

JEL Codes: C25, E61, G18, G21, G51.

The views expressed are those of the author(s) and do not necessarily represent those of the Bank of Lithuania.

Recently, there has been a surge of interest in policies that target climate change. This paper begins by discussing why policymakers, and central banks in particular, should be concerned about climate change, and goes on to argue why carbon pricing is an appropriate political instrument to reduce greenhouse gas (GHG) emissions. The paper details two categories of carbon pricing, namely carbon taxation and the introduction of Emission Trading Systems (ETSs), illustrating why a carbon tax is the more efficient instrument. Popular models for optimal carbon taxation and implications of carbon taxation are discussed. The paper concludes with recommendations to policymakers, which include advocacy of differentiated rather than uniform carbon taxation, phased-in carbon taxation instead of a blanket approach, introduction of the carbon border adjustment mechanism (CBAM), and Green Quantitative Easing (QE).

Keywords: carbon taxation, climate change, green QE.

JEL Codes: Q54, Q58, H23, E51, E62

The views expressed are those of the author(s) and do not necessarily represent those of the Bank of Lithuania.

This paper studies the drivers of wage growth in Lithuania over the period 2008-2020. Using administrative data as well as aggregate measures reflecting the state of the economy, we estimate an extended version of a wage Phillips curve. Our reducedform estimates indicate that nominal wage growth was tightly linked to labor market fluctuation over this period. Labor productivity, changes in the minimum wage, and the composition of employment also contributed to wage dynamics. However, we find little evidence that past inflation has been a push factor. To understand the underlying economic primitives behind our findings, we estimate a structural Bayesian autoregressive model. Our structural analysis reveals a significant contribution from aggregate supply shocks, reflecting a stronger relationship between productivity and wages than implied by our reduced-form estimates. Moreover, the historical decomposition reveals that since 2013, wages grew over and above productivity due to rising aggregate demand and labor market disturbances.

While Euro area interest rates were responding to accommodative monetary policy and decreasing throughout 2015-19, in stark contrast, Lithuania’s bank lending rates increased. Although the rates have slightly dropped around the onset of the pandemic, they are still elevated and well above the EA figures. This paper calls into question, what were the drivers of such interest rate dynamics in Lithuania? By analysing the historical events and practical aspects of loan pricing in Lithuania’s banking industry, we build an empirical model that exploits lending rate variation across banks, time and lending segments, and maps it to different drivers of pricing. We find that the recent changes in lending rates can be attributed to average bank margins, which moved largely in response to changes in market concentration.

Keywords: interest rates, loan pricing, banking, concentration, capital requirements.

JEL Codes: D22, D40, E43, G21, L11.

The views expressed are those of the author(s) and do not necessarily represent those of the Bank of Lithuania.

During the Covid-19 pandemic, house prices and mortgage credit are growing at a long-unseen pace. However, it is unclear, whether such growth is warranted by the underlying market and macroeconomic fundamentals. This paper offers a new structural two-market disequilibrium model that can be estimated using full-information methods, and applied to analyse housing and credit dynamics. Dealing with econometric specification uncertainty, we estimate a large ensemble of the two-market disequilibrium model specifications for Lithuanian monthly data. Using the model estimates, we identify the historical drivers of Lithuania’s housing and credit demand and supply, as well as price and market quantity variables. The paper provides a novel approach in the financial stability literature to jointly measure house price overvaluation and mortgage credit flow gaps. We find that by mid-2021 Lithuania was experiencing a heating in housing and mortgage credit markets, with home prices overvalued by around 16% and the volume of mortgage credit flow being 20% above its fundamentals.

JEL Codes: C34, D50, E44, E51, G21.

The views expressed are those of the author(s) and do not necessarily represent those of the Bank of Lithuania.

The objective of disclosing non-financial information is to create a reliable, transparent and responsible environment and to contribute to long-term sustainable business. This will also contribute to faster economic growth and greater public involvement.

In recent years, with fast climate change and changes in people's lives, the themes of ecology and sustainability have become increasingly more important, with all institutions concerned and investors looking for investments in a cleaner and more transparent environment, even if this reduces their return.

Assessing and improving the sustainability factors – environmental, social and governance (ESG) – is an inseparable part of every company's operations. ESG principles are gradually becoming mandatory. Companies that comply with ESG principles get comprehensive benefits as they are important for all stakeholders: employees, customers, suppliers, investors, etc. In this Overview, the Bank of Lithuania seeks to assess how companies disclose information in their social responsibility reports. In accordance with the Republic of Lithuania Law on Financial Reporting by Undertakings and the Republic of Lithuania Law on Consolidated Financial Reporting by Groups of Undertakings, large public interest undertakings or public interest undertakings – large groups of undertakings, whose average annual number of  employees exceeds 500 as of the last day of the reporting financial year, are required to include the report on social responsibility in the annual report or to prepare a separate report.

In addition, an assessment was made of how companies took into account the 2020 enforcement priorities for financial statements published by the European Securities and Markets Authority (ESMA) related to the disclosure of non-financial information and alternative performance measures (APMs) related to the COVID-19 pandemic.

This Overview assesses the disclosures in the annual reports and corporate social responsibility reports, if any, of the 21 companies listed on the regulated market of AB Nasdaq Vilnius. The scope and specifics of these companies' activities often determine the peculiarities of disclosures (indicators, risks, solutions, etc.). Most companies indicated which European Union (EU) or international frameworks or methodologies they followed. The companies state that they consider themselves to be compliant with the guidelines on sustainable business and that they follow them.

The views expressed are those of the author(s) and do not necessarily represent those of the Bank of Lithuania.

This paper provides empirical evidence on the impact of Covid-19 on unemployment and underemployment in Lithuania. Based on the Labor Force Survey, we document the evolution of the unemployment rate using broader definitions that incorporate the underemployed and marginally attached workers. Our results show that, compared to previous recessions, Covid-19 had a milder impact on the Lithuanian labor market. Moreover, Lithuania fared reasonably well relative to other Eurozone countries. However, the data reveal a substantial increase in marginal workers and underemployment during 2020, with women, young workers and individuals in rural areas being most affected by the pandemic-induced recession.

Keywords: labor market statistics, labor force, unemployment.

JEL codes: E24, J21, J64

The views expressed are those of the author(s) and do not necessarily represent those of the Bank of Lithuania.

Central banks worldwide are grappling with issues relating to data. From how to collect and manage data to aspects of governance, analysis, communication and the proliferation of data – the vast variety of these issues is pushing many to consider root-and-branch reforms. The Bank of Lithuania has been one of the leaders in this regard.

For several years, the Bank of Lithuania has prioritized the development of innovative solutions for streamlining data collection and reporting. These include smart reporting solutions, such as data collection via API, new technologies enabling a switch from aggregate- to granular-level data, and new possibilities for integrating, reusing, and opening up the existing data.

Recently, we took our data management efforts to an even higher level and embarked on the fast track to becoming a truly data-centric organisation by launching an organisation-wide Data Management Maturity Program (DAMAMA). The program activates far-reaching change across the entire data journey within the organisation: data collection, warehousing, analytics, and data governance.

This white paper provides an in-depth guide to the recent data management initiatives at the Bank of Lithuania and the range of complex issues that these initiatives help to solve. In addition, this paper presents the ongoing Data Management Maturity Program DAMAMA, transformation areas covered by the program, main objectives and timelines. Lastly, the final section introduces the international context relating to the ongoing efforts of European organisations to harmonise reporting practices across different domains.

The views expressed are those of the authors and do not necessarily represent those of the Bank of Lithuania.

Foreign trade accounts for a significant part of Lithuania’s economy and the growth of export volumes is a common occurrence in Lithuania, even with rapidly growing wages. With a growth in Lithuania’s exports, the share of exports is also increasing. This indicates that Lithuanian-origin goods and services are competitive in the international market. The competitiveness of Lithuanian-origin exports may be of two kinds: based on the price and costs and based on other, non-price, factors. This article examines two methods of exports competitiveness calculation. When examining exports competitiveness based on the first method, standard formulation for the export equation, regressions are drawn up where exports growth is a dependent variable, whereas demand and the real effective exchange rates (reflecting the impact of prices and costs) are independent variables. Residual variance (i.e. random value) is seen as non-price factors that influence exports growth. When examining exports competitiveness based on the second method, exports of goods are analysed more closely, broken down into four competitiveness groups. The results indicate that the competitiveness of Lithuanian-origin exports in 2001-2019 was essentially determined by factors other than price or costs. In other words, the labour cost growth experienced by exporters is not a key factor that influences the competitiveness of Lithuanian-origin exports.

The views expressed are those of the author(s) and do not necessarily represent those of the Bank of Lithuania.

Available only in Lithuanian

EU’s landmark Next Generation EU programme is an important step forward in both European crisis response and, more generally, EMU deepening, given that the package features elements of both joint debt issuance and fiscal transfers. This paper analyses the programme in comparison to other most prominent joint EMU debt proposals and provides a comparative Scoreboard of the arrangements discussed. It concludes that Next Generation EU falls short of filling in key gaps in the current architecture of the EMU – in particular, the gap laid bare by the lack of a genuine European safe asset. A true “safe haven” instrument – a Eurobond with joint and several guarantees – could move the EMU into a closer alignment with the Optimum Currency Area (OCA) criteria and help compensate for the macroeconomic intra-euro area imbalances. The guarantee structure of the Eurobond, working as an insurance mechanism for Member States’ sovereign debt, would allow for joint debt to significantly strengthen the euro area’s macroeconomic and market stability, the financial sector, or the international role of the Euro. However, issuance of the Eurobond is associated with important moral hazard, political and legal risks, and would most of all require an unprecedented level of trust by Member States.

The views expressed are those of the authors and do not necessarily represent those of the Bank of Lithuania.

The Overview provides key insights into business-wide assessments of money laundering and terrorist financing risks performed by financial market participants. The Overview is based on conclusions obtained by the Bank of Lithuania from the supervision of financial market participants and on an analysis of risk assessments of 20 financial market participants (banks, electronic money institutions and payment institutions) and contains examples of good practice identified during the analysis and cases where risk assessments need to be improved.

This article analyses Lithuania’s investment environment by reviewing investment structure and its changes, assessing the impact of Lithuania’s economic structure on investment performance, revealing the main drivers behind Lithuania’s investment development, showing the interaction between government and business investment and assessing the impact of foreign capital on the country’s economic development. The article shows that the investment to value added ratio in Lithuania is lower than the EU average, which may be partially related to low investment intensity of the main economic activities. It has been identified that the main drivers of investment development in Lithuania are demand variables, such as foreign demand and private consumption. The analysis of government investment revealed that this investment seems to “crowd in” business investment rather than crowding it out. Lithuania’s public infrastructure level is close to the indicator of developed countries, therefore, new investment should be mainly focused on the maintenance of the current infrastructure. In terms of attracting foreign direct investment (FDI), Lithuania is lagging behind other Central and Eastern European countries. The reserves of qualified labour, which made the largest contribution to the attraction of FDI, may be depleted in the medium- or long-term period. The potential for foreign capital inflows could be boosted by the regionalisation processes and value chain shortening highlighted by the COVID-19 crisis as well as by larger-scale digitalisation and automation. The article analyses investment dynamics in Lithuania and reflects its current state, while its future will depend on individual actions of decision-makers and the allocation of limited public and private resources in the right direction.

The views expressed are those of the author(s) and do not necessarily represent those of the Bank of Lithuania.

Available only in Lithuanian

In this Overview, the Bank of Lithuania (LB) aims to assess the way companies disclose information on compliance with the recommendations set out in the principles of the Corporate Governance Code for the Companies Listed on Nasdaq Vilnius (hereinafter – the CGC). In 2017, when Lithuania was pursuing its accession to the OECD, major amendments were implemented in the Republic of Lithuania Law on Companies regarding ensuring the supervisory function of public limited liability companies whose shares are admitted to trading on a regulated market, ensuring the independence of collegial bodies formed by these companies, establishing requirements for transactions with a related party and their disclosure, establishing the shareholder’s right to submit questions to the company in advance, etc. This was also largely due to the recast of the CGC on 15 January 2019, as well as the new form of compliance.

This overview assesses the information disclosed by 26 companies whose shares are admitted to the main and secondary trading lists of Nasdaq Vilnius, AB. The type of activity and specificity of these companies often also determine the specific features of their corporate governance (the structure and composition of bodies, etc.). An assessment of the responses provided by the companies in the reporting form of the CGC with regard to their compliance with recommendations shows that they consider the recommendations to be followed very well (except for principles 5 and 7, where quantitative indicators are lower).

This paper examines the impact of the euro adoption on the economy of Lithuania during its first five years (2015-2019) as a member of the euro area. First, it assesses the impact of the euro adoption in Lithuania on interest rates and real exports, after which it investigates the impact on Lithuanian macroeconomic indicators with a LTDSGE model, using impulse response functions obtained in 2013 in research conducted by the Bank of Lithuania. The paper further estimates the impact of the euro adoption on Lithuanian macroeconomic indicators using the synthetic control method (SCM). The results of this paper confirm the main conclusions of the aforementioned 2013 study, namely, that the long-term benefits of the euro adoption were much higher than the costs, which were mainly short-term or could even be considered as valuable investments. 

JEL Codes: E17, E52, F33, F45

The views expressed are those of the author(s) and do not necessarily represent those of the Bank of Lithuania.

Available only in Lithuanian

We use survey micro-data for 31 European countries, and estimate the life-cycle profiles of worker transition probabilities across employment, unemployment and nonparticipation. The estimated transition probabilities are then used to explain aggregate difference in employment rates between Lithuania and Europe. We show that the separations from employment is a key in understanding differences in labor market outcomes of both genders, and that demographics play a large negative role for Lithuanian employment rates. The results have important implications for economic policies that are discussed at the end of the analysis.

The views expressed are those of the author(s) and do not necessarily represent those of the Bank of Lithuania.

The views expressed are those of the author(s) and do not necessarily represent those of the Bank of Lithuania.

Available only in Lithuanian

Available only in Lithuanian

The topic of central bank digital currency (henceforth - CBDC) has recently gained significant share of attention among policy makers and academics. A wide range of CBDC setups are discussed from the universally accessible central bank accounts or digital tokens to less extreme suggestions of only partly broadening central bank balance sheet access by providing CBDC to wholesale consumers or getting private sector to mediate in the process by providing synthetic CBDC.

This paper recalls the possible CBDC implementation types that are discussed in the current context; reviews some of the discussions among those researching the topic; gives a brief overview of the next-step initiatives taking place among central banks with a potential to lay ground for the practical CBDC implementation; and discusses the main policy implications from financial stability and monetary policy perspectives.

The views expressed are those of the author(s) and do not necessarily represent those of the Bank of Lithuania.

Timely monitoring of the housing market developments in Lithuania is one of the key elements in the analysis framework of the macroprudential authority aiming to contribute to financial stability in Lithuania. In this paper, we addressed three important questions related to Lithuanian house prices, namely, whether house prices are under- or over valuated, which explanatory variables have the biggest impact on the growth of house prices and what the future development of the Lithuanian house price index could be. Three separate modelling and forecasting exercises were performed in order to tackle these questions. The first exercise employs the vector error correction modelling (VECM) approach to assess under- or overvaluation of the house prices. We then use an autoregressive distributed lag model (ARDL) to evaluate which explanatory variables have the biggest impact on house price growth. As the last exercise, we develop a suite of models that are used to forecast future development of the house price index. The analysis presented in this paper may be viewed as a further step towards more formalised modelling and forecasting of the Lithuanian house price index.

JEL Codes: C22, C32, C53, E37, R30.

The views expressed are those of the author(s) and do not necessarily represent those of the Bank of Lithuania.

This paper overviews early research which has gone into the possible effects of the recent tensions in international trade. We have witnessed the increase and the promises of future increase in tariffs, in the case of the new trade policy of the US, and the promises of the future increase in the non-tariff barriers (possibly even tariffs) in the UK’s decision to leave the EU. The focus in the research is mostly on trade policy and on the results, insights, and conclusions, while the discussion on the econometric specification or estimation of the models is out of scope.

The views expressed are those of the author(s) and do not necessarily represent those of the Bank of Lithuania.

This paper examines the implications of digital currencies – both private cryptocurrencies and central bank digital currencies (CBDCs) – for central banking. We discuss some déjà vu episodes from monetary history in order to obtain a clearer understanding the present and potential implications of these currencies. We find that not only the current limitations of private cryptocurrencies, but also their conceptual underpinnings, argue against their replacement of conventional money. The two main potential problems with broadly accessible (general purpose) CBDC are a digital run and an excessive involvement of a central bank in the funding of the real economy. Meanwhile, alternative reserve-backed accounts or tokens (an implicit CBDC known as Tobin’s alternative) would also be exposed to these problems, albeit in a less pronounced way. CBDC-related hopes for monetary policy to eliminate the effective lower bound constraint are found to be exaggerated, even in a cashless world. We argue that central banks’ response to the digitalisation trend should be an integrative solution which satisfies the public demand for a safe means of payment, safeguards private innovations, and ensures financial stability. We conclude that there is no observable form of CBDC that would serve as a best-choice central bank response in advanced economies. Such a response might be considered as a temporary solution (if any), however, in emerging economies with weak financial inclusion. 

JEL Codes: E51, E58, N20.

The views expressed are those of the author(s) and do not necessarily represent those of the Bank of Lithuania.

The Eurosystem started its asset purchase programme (APP) in March 2015. Net purchases were carried out until the end of 2018, while since the beginning of 2019 only reinvestments are being made. The APP consists of the public sector purchase programme (PSPP), third covered bond purchase programme, asset-backed securities purchase programme and corporate sector purchase programme. The Bank of Lithuania is participating in the PSPP by purchasing Republic of Lithuania government securities (GS), issued in domestic and international markets and debt securities issued by European supranational issuers. Seeking more effective and transparent purchases, the Bank of Lithuania made a decision to purchase domestic Lithuanian GS by implementing reverse auctions. The paper introduces reverse auctions in the context of monetary policy operations, the Bank of Lithuania’s purchase framework of reverse auctions, and examines the purchases of domestic Lithuanian GS by the Bank of Lithuania in the period of March 2015–June 2018.

The views expressed are those of the author(s) and do not necessarily represent those of the Bank of Lithuania.

Available only in Lithuanian

Euro area countries have experienced profound economic, financial and institutional changes over the last three decades. GDP growth has been very volatile, and very uneven, across countries. Which factors played a role in stirring growth and/or reducing it?  We provide an atheoretical toolkit looking at a large set of real, financial, monetary and institutional variables, as possible factors behind fluctuations and differences in growth rates among euro area countries since 1990. The main outcome stresses the key positive role for long-run growth of higher European institutional integration, overall and for the periphery in specific. This result is robust across specifications and setups. If we split the European institutional integration in its main components, we can see a significant positive role for financial and political integration in the long-run. However the first seems to have beneficial effects for the core only while the opposite holds for the political integration which influences positively the periphery.

The views expressed are those of the author(s) and do not necessarily represent those of the Bank of Lithuania.

The views expressed are those of the author(s) and do not necessarily represent those of the Bank of Lithuania.

Available only in Lithuanian

The views expressed are those of the author(s) and do not necessarily represent those of the Bank of Lithuania.

Available only in Lithuanian

In the aftermath of the financial crisis, Lithuania‘s banking sector faced structural changes related to higher concentration, decreased interconnectedness and lower risk appetite. At the same time banks were able to maintain strong profitability levels measured by the EU standards largely due to increased efficiency, very low funding costs, reduced impairments and stable commission income. This paper describes the banking sector of Lithuania in the post-crisis environment and argues that the post-crisis structural changes in general had positive effects on the banking sector’s resilience and in the first instance on profitability. In particular, high concentration of the sector was likely to help banks achieve higher efficiency while reduced risk tolerance had direct positive effects on lower impairments as well as indirect effects on lower funding costs. On the other hand, good profitability of the sector has been largely dependent on two largest market participants while smaller banks and branches had less prosperous profitability prospects. In the environment where large banks appear to have particularly good cost management practises, the possibilities for entry of new market players of significant size are plausible only if the newcomers are able to reach the prevailing level of high efficiency. However, without a sizeable market share this might be difficult to achieve.

The views expressed are those of the author(s) and do not necessarily represent those of the Bank of Lithuania.

By resorting to the analytical integrated accounts framework, this paper investigates the relationship between economic and financial imbalances during the recent economic and financial cycle in Lithuania. There is clear evidence from the financial accounts data that there was a pronounced expansion of balance sheets of institutional sectors during the phase of the economic upturn, whereas the economic downturn was essentially a balance-sheet recession characterised by contracting private sector balance sheets and the reversal in credit flows and monetary dynamics. The boom-and-bust cycle was strongly associated with exuberant bank lending during the boom years, followed by a sudden reversal of lending conditions and the subsequent repatriation of debt financing by foreign banks.
The Lithuanian experience also confirms that strong credit and asset price boom accompanied by economic imbalances, and debt financing of current account deficits in particular, is a potentially risky mix of economic conditions. The policy response to crisis was a market-imposed austerity but nevertheless there was a sharp rise in public debt, essentially offsetting deleveraging in the private sector. The effective replacement of growth of private sector debt with a rapid accumulation of public debt was a very important stabilising factor.
Certain characteristics of bank credit (namely, its partial self-financing) imply that under some conditions economic stabilisation could have been achieved through domestic financing. However, the government had to resort to foreign financing, which was rather costly. During the crisis the monetary dynamics was driven by government borrowing from abroad, stepped up capital transfers from abroad and positive current account adjustments, all of which allowed foreign parent banks to withdraw debt financing and replace it with domestic deposit financing.

The views expressed are those of the author(s) and do not necessarily represent those of the Bank of Lithuania.

To analyse inflation in Lithuania and determine inflation trends in the long run, the paper identifies long-term factors, namely the Eurosystem’s monetary policy and economic convergence. The main objective of the Eurosystem is to maintain price stability, defined as annual inflation rates below, but close to, 2% over the medium term. However, due to economic convergence, inflation rates of Central and Eastern European (CEE) countries can be around 1 to 3 percentage points higher than, for example, those of the older EU Member States. This is influenced by the participation in the EU single market, which promotes equalisation of prices and wages in the EU, and the fact that less developed countries of the EU exhibit relatively more rapid economic growth. The latter determines the convergence of the CEE countries’ income levels with the income levels of the more developed EU countries, and adds further pressure on inflation.
Lithuania’s inflation dynamics over the analysed period were also underpinned by various factors that caused inflationary fluctuations in the short and medium period, for example, domestic and foreign economic activity, international commodity prices, and administrative decisions. All these factors boosted inflation in 2017. Growth of food and beverage prices in 2013–2017 amounted to around 2.2% on average, reaching 5.5% in 2017. This increase was driven not only by the growth of food commodity prices, but also by a large increase of excise duties on alcoholic beverages. Service price growth in 2013–2017 reached around 3% on average, whereas in 2017 it accelerated to 5.5%. More rapid growth in prices of services in 2017 can be explained by the prevailing tensions in the labour market: a shortage of labour force, which has put pressure on wages, and a noticeable rise in the minimum monthly wage. Although the long-term growth rate of non-energy industrial goods has been close to 0, recent improvements in the international environment and rapid growth of unit labour costs have led to an increase in corresponding prices. Finally, the development of oil prices has had an indirect effect on the evolution of the prices of all inflation components in both the short and the medium term.
Countercyclical fiscal policies might improve the management of the economic cycle and inflation. Given that all euro area countries are under the Eurosystem’s monetary policy framework, a sustained fiscal policy would help to minimise inflationary deviations from the long-term trend of domestic economic factors. In terms of fiscal policies, the economy should not be further stimulated during an economic upturn (for example, through tax cuts or cost increases); government revenue surplus collected during cyclical upturn should be set aside in case of a downturn, thus preserving the volume of domestic demand.
When inflation fluctuations are disadvantageous to consumers, i.e. when revenue is growing at a slower or similar pace as prices, the purchasing power of the lowest–income households should be ensured. For the low–income citizens, economic benefits brought by growing economy can be insufficient or overdue. Therefore, the purchasing power of consumers with the lowest income can be maintained through structural reforms, for example, a thorough tax system reform. With such a reform, the share of GDP reallocated should be increased. Also, in order to increase GDP reallocation, significant changes in the tax system should not be carried out in isolation, i.e. restructuring of the pension system should come hand in hand.

The views expressed are those of the author(s) and do not necessarily represent those of the Bank of Lithuania.

Available only in Lithuanian

This paper aims to explain the relationship between risk-based and leverage ratio (LR) requirements and the motivation for the macroprudential use of LR requirements.

The LR requirement is part of the Basel III reform, and it will be introduced as a Pillar 1 standard to supplement the existing risk-based capital requirements. Since 2015, the disclosure requirement has been in place, and banks have to regularly compute and report their LR. Both the BCBS and the EBA have confirmed that the minimum microprudential LR requirement of 3 per cent is appropriate and should become mandatory. A minimum LR requirement will act as a backstop for risk-weighted capital requirements, by ensuring that a financial institution has a minimum level of equity.

A minimum LR requirement serves as the ultimate backstop against the shortage of equity based on risk-weighted capital requirements. The LR limits the exposure a bank can accumulate in relation to existing capital. It is calculated by dividing the amount of high-quality capital of a financial institution by its total non-risk-weighted exposure. The LR requirement adds an important backstop to the situation when observed risk levels differ significantly from actual unobserved levels, which could materialise quickly. There are merits to using LR requirement add-ons on a macroprudential basis as the internationally agreed-upon LR minimum (3%) might be an insufficiently effective addition to the robust capital framework. A handful of countries, such as the UK, US, Norway and Switzerland, use LR add-ons applied on top of the minimum microprudential LR requirement. However, none of the countries thus far follow a single, common framework when it comes to setting the LR requirement. In addition, when one takes into account recent research on optimal risk-weighted capital levels, the internationally agreed-upon minimum LR requirement of 3 per cent seems to lack effective backstopping power.

The views expressed are those of the author(s) and do not necessarily represent those of the Bank of Lithuania.

The analysis of estimates of sustainability indicators of general government finances shows that the mid-to-long term risk to the sustainability of Lithuania’s general government finances is higher than the respective risk for Latvia or Estonia. The lower score results from the impact of ageing-related expenditure, the bulk of which goes towards pension benefits. However, the previous estimates of sustainability indicators of general government finances do not take into account the changes to Lithuania’s state social insurance system, which were adopted in 2016 and will come into effect in 2017 and 2018. The analysis shows that when taking into account these changes, the evolution of old-age pension expenditure in Lithuania becomes more aligned with the expected developments in other Baltic countries hence the country’s fiscal sustainability score should become similar as well.
Long-term developments in the ratio of old-age pension expenditure to GDP are driven by demographic factors, factors stemming from pension arrangements as well as the country’s macroeconomic situation. Population ageing-related factors will put upward pressure on pension expenditure in all three Baltic countries in the long term. This impact, however, will be offset by the decreasing generosity of the pension system, the rising retirement age and the increasing employment rate. As a result, the old-age pension expenditure-to-GDP ratio will decrease by 2060 in all Baltic states.
Even though the situation of pension systems of all Baltic countries may look sustainable in the long term from a formal point of view, i.e. when measured in terms of financial flows (the ratio between pension expenditure and GDP will decrease by 2060), the key factor underlying sustainability, i.e. the decreasing ratio of the average pension to the average wage, raises serious doubts. This ratio implies a substantial future decrease in the generosity of the pension system and insufficient adequacy of old-age pensions. The assessment of fiscal sustainability, which disregards the adequacy of the pension system, is too narrow and limited. The anticipated low old-age pension-to-average wage ratio might act as a deterrent to participation in the social insurance system. Therefore, the authorities would likely end up seeking resources to increase pensions, which would undermine fiscal sustainability. In a scenario which implies no change in the old-age pension replacement rate from its current level and which looks the most feasible due to political risks, Lithuania’s fiscal sustainability score is likely to be lower than estimated by the European Commission, which points to the need to take measures that could ensure fiscal and social sustainability.
The alternative scenario analysis of Lithuania’s pension expenditure–to-GDP ratio indicates that some measures could partly offset the effect of ageing. The analysis of various demographic scenarios indicates that population ageing is inevitable in Lithuania, i.e. the proportion of older persons in the population will increase compared to the proportion of the working age group. This implies that an increasing share of the budget will have to be allocated for old-age pensions and that the replacement rates of the first pillar pensions will be negatively affected. Such measures as increasing labour market activity, promoting employment, and raising the retirement age could increase sustainability of Lithuania’s pension system in the long term.

The views expressed are those of the author(s) and do not necessarily represent those of the Bank of Lithuania.

Available only in Lithuanian

Empirical evidence suggests that investments in research and development (R&D) by older and larger firms are more spread out internationally than R&D investments by younger and smaller firms. In this paper, I explore the quantitative implications of this type of heterogeneity by assuming that incumbents, i.e. current monopolists engaging in incremental innovation, have a higher degree of internationalization in their R&D technologies than entrants, i.e. new firms engaging in radical innovation, in a two-country endogenous growth general equilibrium model. In particular, this assumption allows the model to break the perfect correlation between incumbents’ and entrants’ innovation probabilities and to match the empirical counterpart exactly.

JEL Codes: E22, F31, G12, O30, O41.

The views expressed are those of the author(s) and do not necessarily represent those of the Bank of Lithuania.

In this paper, we examine the relationships between real, credit and house price cycles, by using a synchronicity index, and structural characteristics and macroeconomic variables of 17 EU countries. We find that the cycles between credit variables and the real cycle with the property or equity prices cycles seem relatively well synchronised. Credit and GDP fluctuations seem to be less synchronised, mostly because credit volumes tend to lag the real cycle by several quarters. The high rates of private homeownership tend to be associated with larger cycles in GDP, credit, and house prices. Higher Loan-To-Value ratios, seen as a proxy of borrowing constraints, and a higher percentage of flexiblerate mortgages, could also indicate that a country is more sensitive to shocks and possibly increase pro-cyclicality and increase cycle volatility. Finally, the pro-cyclicality of the credit and housing market to the GDP cycle can be linked to the fluctuation in current accounts and their misalignments with respect to the theoretical equilibrium value. The synchronicity and the cycles of credit may also be considered for signaling recessions.

JEL Codes: E32, E44, F36.

The views expressed are those of the author(s) and do not necessarily represent those of the Bank of Lithuania.

The paper discusses monetary policy stance assessment in times of both conventional and unconventional monetary policy. Prior to the financial crisis, many central banks had one primary target and one instrument, the short-term rate. Over the years there was a consensus that the rule-of-thumb characterization known as the Taylor rule could broadly outline the policy and supplement discretionary policy. In the post-crisis period, one instrument was no longer sufficient and unconventional measures, such as large-scale asset purchases and forward guidance, were put in the policy makers’ agendas. Therefore, assessing the impact of the implemented unconventional measures and understanding the overall monetary policy stance in traditional ways no longer suffices, while finding new suitable ways is not an easy task. The shadow rate literature is able to circumvent the lower bound constraint and incorporate the monetary policy accommodation provided by the asset purchase programmes. However, application of the shadow rate estimates, in order to assess monetary policy stance, has to be done with caution since the estimates lack robustness.

The views expressed are those of the author(s) and do not necessarily represent those of the Bank of Lithuania.

In this paper we provide an overview of the different approaches identified to capture monetary policy in a period of Zero Lower Bound (ZLB). We focus here on the methods closely linked to interest rates, which include: spreads, synthetic indices from principal component analysis and different shadow rates.
In the second section of this review we calculate these measures for the euro area and also draw comparisons among different approaches and look at the effects on main macroeconomic variables, with a special focus on inflation. The impact of unconventional monetary policy shocks on inflation is found to be significantly positive by the majority of the studies and by using different methods.
Ultimately, we provide a summary of the literature on the Natural Real Rate of Interest, which may be useful for assessing how long low (real) interest rates in a ZLB may stay in place; also suggesting some possible improvement in the estimations which would lead to more accurate policy recommendations.

JEL Codes: E43, E52, E58, F42.

The views expressed are those of the author(s) and do not necessarily represent those of the Bank of Lithuania.

Each time researchers jointly write an article, a decision must be made about the order in which the authors are listed. There are two main norms for doing so. The vast majority of scientific disciplines use a contribution-based norm according to which authors who contributed the most are listed first. Very few disciplines, most notably economics, instead resort primarily to the norm of listing authors in alphabetical order. It has been argued that (i) this alphabetical norm gives an unfair advantage to researchers with last names starting with a letter early in the alphabet and that (ii) researchers are aware of this “alphabetical discrimination” and react strategically to it, for example through avoiding collaborations with multiple others. This article surveys the empirical literature on these two related topics. Overall, there is convincing evidence that alphabetical discrimination exists and that researchers react to it.

The views expressed are those of the author(s) and do not necessarily represent those of the Bank of Lithuania.

In this paper, we look at the determinants of current accounts in twenty-seven EU countries over the period 1994-2014. The twenty-seven countries of interest are divided into three sub-groups, namely: core, periphery and CEE new member states. We also assess the current accounts based on computed equilibrium values, and we provide a measure of misalignment for the medium run. As determinants we include capital flows as well as demographic, fiscal and relative development factors. The initial Net Foreign Asset position and oil balance seem to matter more in the core countries than in the periphery and CEE new member states. In contrast, the periphery and CEE new member states seem to be more strongly affected by capital flows. Fiscal balance negatively affects only the periphery, while an increase in government spending is positive for the current account for CEE new member states. In the past twenty years these misalignments have shown a cyclical behaviour in most EU countries, and the magnitude of the cycles themselves are highly heterogeneous across groups. Lastly, we compute an adjusted current account equilibrium, which tries to correct the equilibrium value by the role of expectations (proxied by IMF projections). This factor has more of an impact in the UK than in the euro-area countries.

JEL Codes: F32, F31, C33.

The views expressed are those of the author(s) and do not necessarily represent those of the Bank of Lithuania.

We extend the endogenous growth model of Kung and Schmid (2015) by adding endogenous labor dynamics and wage rigidities. This leads to an increase of about 250 basis points in risk premia. Additionally, it brings labor market quantities much closer to their empirical counterparts. In particular, wage rigidities generate an increase of around 60 basis points in labor growth volatility.

JEL Codes: E22, G12, O30, O41.

The views expressed are those of the author(s) and do not necessarily represent those of the Bank of Lithuania.

We built different financial cycle measures, also applied recently in Comunale and Hessel (2014).
Our aim is to provide a comprehensive database with definitions of variables that may be of use for crosscountry comparative analysis.
The database includes 41 countries (EU28 and OECD members) from 1994 to 2014 with both annual and quarterly frequency.
The main contributions of our database are that: i) it is publicly available and freely downloadable from the website of the Bank of Lithuania and it can be used subject to a clear reference; ii) the data are updated to the most recent year/quarter available; ii) considers not only the EU members as of 2014 (Croatia is therefore included in the sample), but also other non-EU countries part of the OECD (including both advanced and developing economies); iii) is built using both HP filtering techniques and the Principal Component Analysis (PCA), the latter are used to compute synthetic indices, to come up to different applicable indicators; iv) we added also some business cycle measures for comparison reason.
Ultimately, we show an application of our data, checking whether the financial cycle can influence the estimation of inflation in the euro area and what is the difference between adding a business or a financial cycle measure for the exchange rate pass-through (ERPT). We find that the ERPT can be higher in the presence of house price fluctuations at the frequency of the financial cycle. 

JEL Codes: E32, E44, F36.

The views expressed are those of the author(s) and do not necessarily represent those of the Bank of Lithuania.

This paper gives a broad descriptive overview on wage and price setting behaviour of Lithuanian firms during the last episode of the economic crisis in 2008–2009 and in the post-crisis period of 2010–2013. The evidence provided in this paper is based on the firm-level data from the third wave of the Wage Dynamic Network (WDN3) survey — the joint research project of the European Union (EU) countries launched within the European System of Central Banks (ESCB). Wage and price setting strategies of Lithuanian firms were evaluated by relating firms’ decision-making to the macroeconomic, financial and institutional environment under which the firms are operating. The preliminary conclusion drawn in this paper is that both wages and prices show rather high degree of flexibility in Lithuania. Low wage rigidity should primarily be attributable to labour market institutions — low collective wage bargaining coverage and completely decentralised wage setting process. Easing of employment protection laws during the last episode of economic downturn might also have contributed to the increased wage flexibility in the after-crisis period.

The views expressed are those of the author(s) and do not necessarily represent those of the Bank of Lithuania.

The central question of this paper is how international trade and specialisation are affected by different designs of pension schemes and asymmetric demographic changes. In a model with two goods, two countries and two production factors, we find that countries with a relatively large unfunded pension scheme will specialise in the production of labour intensive goods. If these countries are hit by a negative demographic shock, this specialisation will intensify in the long run, which is contrary to the prediction of the classical Heckscher-Ohlin-Samuelson model. Eventually, these countries may even completely specialise in the production of those goods. The effects spill over to other countries, which will move away from complete specialisation in capital intensive goods as the relative size of their labour intensive goods sector will also increase. 

JEL Codes: E27, F16, H55, J19.

The views expressed are those of the author(s) and do not necessarily represent those of the Bank of Lithuania.

This paper discusses a bootstrap-based test, which checks if finite moments exist, and indicates cases of possible misapplication. The analysis indicates that a procedure for finding the smallest power to which observations need to be raised, such as the test rejects a hypothesis that the corresponding moment is finite, works poorly as an estimator of the tail index or moment estimator. This is the case especially for very low- and high-order moments. Several examples of correct usage of the test are also shown. The main result is derived analytically, and a Monte-Carlo experiment is presented.

MSC2010 Codes: 62G10, 65C05.

The views expressed are those of the author(s) and do not necessarily represent those of the Bank of Lithuania.

Since the crisis in the Baltic countries in 2009, the question on the particularities of business models adopted by foreign-owned banks has been often raised. The business models of these banks have changed significantly, but they still remain of major concern. The aim of this paper is to identify what type of business models have been chosen by the Baltic foreign-owned banks, to assess them as well as to provide recommendations on how to address the outlined challenges.
The Literature Review showed that the Business Model Canvas approach can be used for bank business model analysis. However, banking specialness should be taken into account. Empirical research was carried out using a combination of qualitative and quantitative methods for nine Scandinavian banks subsidiaries operating in the Baltics. The main focus of this research was the complex analysis of bank business model components, using the newly created system of key business model indicators. Business model analysis was based only on publicly available information, which is limited and not standardised.
The main characteristics of the business model of Scandinavian banks subsidiaries established in the Baltics are as follows: retail banks operating in one jurisdiction, dependency on the parent bank decisions, aversion to risk, stronger focus on non-interest income and high efficiency due to cost cutting and e-banking, orientation on safety (banks meet prudential requirements with large reserves), and medium profitability with a negative trend for the future. It was determined that if banks keep on doing their business as they are currently, their possibilities of generating acceptable returns will be of major concern. The biggest opportunity for banks in a low interest rate environment is to focus on increasing the volume of interest bearing assets. Financing small and medium-sized enterprises (SMEs), especially in productive sectors and innovative companies, could be the best outcome for banks and Lithuania’s economy. To achieve this goal, banks need to set SMEs financing as a strategic priority, make fundamental changes in their lending policy. The EU and local governments should give financial support for SMEs to strengthen this sector, and that should encourage banks to finance SMEs more actively as well.
The analysis of bank business models is a relatively new approach towards banking industry analysis. This paper is the first attempt of deeper analysis of business models of Scandinavian banks subsidiaries operating in the Baltics. This paper can serve as an eye-opener for Financial Supervisory Authorities and Central Banks, Scandinavian banks when drafting strategies for their subsidiaries and Government representatives who are responsible for the banking system strategy and strengthening SMEs sector.

JEL Codes: G21, M21.

The views expressed are those of the author(s) and do not necessarily represent those of the Bank of Lithuania.

This paper presents the analysis of indicators that could signal the build-up of systemic risk in Lithuania during the periods of credit expansion. The resulting set of early warning indicators could be useful in operationalizing countercyclical macroprudential policy measures, especially the countercyclical capital buffer (CCB). It could serve as a starting point in considerations whether there is a need to increase banks’ resilience in the upturn of financial cycle by accumulating additional capital buffers.
Taking into account the short Lithuanian data series which cover only one systemic banking crisis period, the analysis is extensively based on international research, particularly on findings of the European Systemic Risk Board (ESRB) Expert Group which provided analysis for the ESRB Recommendation on guidance on setting countercyclical buffer rates (ESRB 2014/1). Consistent with the existing research, we show that the deviation of the ratio of credit to gross domestic product (GDP) from its long-term trend (credit-to-GDP gap) is a suitable early warning indicator of financial crises in Lithuania. However, gap estimation faces uncertainty as the long-term trend is unobservable. To deal with the uncertainty, the estimation of the long-term trend was augmented with forecasts and most suitable alternative to the so called standardised ‚Basel gap‘ (suggested by the BCBS) is provided. In addition to this, complementary early warning indicators have been selected that could give concise yet comprehensive and robust view of the state of the Lithuanian economy. The performance of selected early warning indicators has also been evaluated for the three Baltic states (Lithuania, Latvia and Estonia).

JEL Codes: C40, G01.

The views expressed are those of the author(s) and do not necessarily represent those of the Bank of Lithuania.

The article examines the usefulness of six sector-based confidence indicators in forecasting Lithuanian short-term sectoral economic activity. All six sentiment indicators are examined side-by-side, which allows us to compare their properties, informational content and marginal contribution in forecasting. One of the properties common to all the confidence indices is that the confidence indices’ levels are more related to annual activity changes than to quarterly changes, which motivates us to take into account as well the change in the confidence index level. We find consumer, construction, and economic sentiment indicators to be the most reliable of the six indices, while the manufacturing sentiment index was the least useful in forecasting. We assess the marginal impact of the indicators, employing factor models augmented by additional regressors. Our results also suggest that information on sentiment in one sector is useful in forecasting activity of other sectors as well. The relationship between consumer confidence and private consumption seems to be a somewhat more interesting case than the others, as the level of consumer confidence is statistically significant in regressions when other available economic information is already taken into account. Our interpretation is that the consumer confidence indicator is a proxy of a structural consumption parameter, such as marginal propensity to consume.

JEL Codes: C33, C53.

The views expressed are those of the author(s) and do not necessarily represent those of the Bank of Lithuania.

This paper analyses the link between migration and sizes of countries. It explains why larger countries (in terms of population) have lower shares of migrants in their populations. First, the data is analysed; next, a macroeconomic model with international trade and migration, explaining the stylised facts, is developed. The model includes country size, which gives rise to cheaper country-specific goods produced in a large country relative to the goods produced in a smaller country. Higher wages in the small country spur immigration to it.

JEL Codes: F16, F22.

The views expressed are those of the author(s) and do not necessarily represent those of the Bank of Lithuania.

In the recent debate about the channels for growth there are two different aspects to take into account: the importance of the exports in services and the sophistication of the exports themselves. We analyze in this paper the situation of exports in Lithuania, highlighting the modern/high-tech sectors with a special focus on services.
We found that the percentage of high-tech merchandise exports on the total exports increased in general the last decade, from less than 4% of total merchandise exports to more than 10%.The exports in modern services are instead the only one which experienced a positive growth rate in the worst period of the crisis (2009). Looking at the foreign demand for services, especially for modern services, this changed a lot in the last decade. The main partner for modern services now is Germany, while for total service exports the first destination is Russia, as it is for total goods. For total goods other countries not in the EU mattered more in 2004 than nowadays. Non-EU countries are becoming crucial for exports in modern services.
In addition, we provide a simple econometric setup in which we study the impact on the different type of real exports of the Real Effective Exchange Rate (REER, deflated in several ways) and the trade-weighted (weighted for trade in services and in goods) foreign demand based on real GDP data or Gross Value Added. The exports of modern services seem to be not explained by the competitiveness or demand factor. In our setups the main determinant is the exports in the previous period. The outcome for modern services is quite robust across the specifications and with different REERs. The exceptions concern the setup with GDP foreign demand estimated by OLS, in which also the foreign demand seems to play a role for exports in modern services. For exports in total services and traditional services instead, foreign demand matter in more cases and using different REERs especially with a more general measure of foreign demand based on real GDP.
The REER for goods and services exports matters more if deflated by CPI both in case of GDP and Gross Value Added-based foreign demand, and mostly in the short-run.

JEL Codes: F14, F43, C22.

The views expressed are those of the author(s) and do not necessarily represent those of the Bank of Lithuania.