Bank of Lithuania
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No 52
2024-02-28

Commercial real estate risk supervision framework

  • Abstract

    Similar to eurozone as a whole, in Lithuania, the commercial real estate sector is closely linked with the financial system and the real economy: loans secured by commercial properties account for almost a third of the total bank loan portfolio, and the development of housing and other buildings creates about an eighth of Lithuania's GDP. However, so far both in Lithuania and across Europe, this sector has been supervised quite unsystematically, and the lack of harmonized indicators and data complicates monitoring at the international level. Aiming to ensure timely identification of risks to financial stability and improve international data comparability, the Bank of Lithuania, following the ESRB recommendation and methodology, has developed a commercial real estate market supervision framework. The main purpose of this article is to presents the developed framework. The article, alongside specific guidelines on how to consistently assess risks arising from the commercial real estate market, discusses methodological and data gaps that continue to pose challenges in ensuring a comprehensive risk assessment.

     

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


    Available only in Lithuanian

No 51
2024-02-20

State guarantees for loans to small and medium-sized businesses

  • Abstract

    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

No 50
2024-02-15

Anatomy of inflationary shock in Lithuania: causes, effects and implications

  • Abstract

    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.

No 36
2024-01-24

Loans vs Subsidies: Lithuania’s State Support Policies During the COVID-19 Pandemic

  • Abstract

    This paper analyzes the firm’s choice between subsidy support and loan support during the COVID-19 crisis and explores the implications of this choice on firms’ employment growth. We compile a novel micro-level dataset of Lithuanian firms’ balance sheet data and government support records during the pandemic period. We use the dataset to provide a set of stylized facts, categorizing the variety of enacted support policies and tracking aid distribution patterns. We show that larger firms were more likely to choose loans over subsidies. This result cannot be fully explained by policy eligibility criteria and the severity of the pandemic shock, suggesting that firm characteristics played a significant role. Finally, we show that the type of support has implications for firms’ outcomes – subsidy-recipient firms experienced higher employment growth compared to loan-recipient firms.

No 49
2024-01-22

Overview of Issuers’ Non-financial Information in Accordance with the Disclosure Requirements of Article 8 of the Taxonomy Regulation

  • Abstract

    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.


    Available only in Lithuanian

     

     

     

No 35
2024-01-09

Mergers and Acquisitions Over the Cycle – An Empirical Investigation

  • Abstract

    Using US firm-level data from 1985-2019, this paper investigates how the characteristics of matches between acquirers and targets of mergers and acquisitions (M&A) vary over the business cycle. We document several findings. (1) Acquirers are on average larger, more profitable, and in a stronger financial position than targets. (2) Targets are more innovative than acquirers, and (3) M&A targets during a recession have worse financial health but higher levels of innovation compared to M&A targets in booms. Our empirical evidence suggests that an economy may benefit from an economy may benefit from adjusting its antitrust stance over the business cycle.

    Keywords: mergers, M&A, business cycle, R&D, productivity

    JEL codes: E22, E32, G34

No 119
2024-01-05

The transmission of trade shocks across countries: firm-level evidence from the Covid-19 crisis

  • Abstract

    This paper studies the margins and heterogeneity of adjustments to trade shocks by estimating how Covid-19 restrictions affected imports and exports. We use data from Lithuania, Latvia and Estonia on foreign trade at the level of the firm and the partner country and at monthly frequency from January 2019 to December 2020. The focus is on the short-term adjustment and on the first wave of the pandemic. We find that the adjustment to the restrictions mostly occurs through the intensive margin, meaning trade values are reduced rather than trade in certain markets or products ceasing. It is further observed that quantity played a more important role in the adjustment process than prices and that both upstream and downstream restrictions played an equally important role in the decline of foreign trade. It is shown that differentiated products that are difficult to replace are responsible for this adjustment pattern.

    Keywords: transmission of shocks, input-output linkages, global value chains, Covid-19, workplace closing.

    JEL codes: F14, F61, D22

No 34
2023-12-31

Consumer price rigidity in periods of low and high inflation: the case of Lithuania

  • Abstract

    I provide new monthly statistics on consumer price rigidity in Lithuania. The statistics are derived from CPI price records, covering an average of 90% of the ECOICOP4 weights between 2019 and 2023. Through a comparative study of two distinct periods – low inflation from January 2019 to December 2020, and high inflation from January 2021 to March 2023 – a significant shift in the frequency of price changes is observed in the latter period. This shift is mainly due to a significant rise in the frequency of price increases, while the average size of these increases has remained relatively constant over the years. Furthermore, I show that structural aggregate demand and energy shocks induced shifts in the frequency of price changes during the high-inflation period, suggesting that state-dependent sticky price models may be more suitable than time dependent ones for explaining inflation fluctuations in Lithuania.

    Keywords: consumer price rigidity, price-setting, high inflation, frequency of price changes.

    JEL codes: D40, E31, E50

No 33
2023-12-30

Household Wealth and Finances in Lithuania

  • Abstract

    This report presents the stylized facts gathered in the fourth wave of the Eurosystem Household Finance and Consumption Survey, which was conducted in Lithuania as the second wave of results. The survey provides household-level data on wealth, finances, consumption, savings, and additional individual characteristics, covering a sample of 1,664 households. Although the reference period for the data varies across countries, for Lithuania, it pertains to 2021. The report compares new results with those from the previous survey conducted in 2017. The results indicate an increase in measures for household wealth and finances that were only minimally affected by the COVID-19 pandemic.

    Keywords: Household-level data, assets, liabilities, net wealth, financial pressure, consumption

    JEL codes: D12, D14, D31

No 32
2023-12-29

Climate Risk and Bank Capital Structure

  • Abstract

    We study the role of climate risk exposure in the dynamic behavior of banks’ regulatory capital adjustment using a large European sample from 39 countries during the 2006–2021 period. We find that banks facing high exposure to climate risk opt for a higher target (regulatory) capital adequacy ratio and make faster adjustments to their optimal capital structure, especially if they are more exposed to carbon pollution. Such banks boost their adjustment during the post-Paris Agreement period. These banks move to their target capital adequacy ratio mainly by adjusting their risk-weighted assets or by reallocating them more quickly than their peers, without necessarily altering assets, particularly lending. This paper lends support to the importance of taking climate change-related risks into prudential supervision to protect the financial system’s resilience and contributes to the debate on climate-related capital requirements.

    Keywords: Dynamic capital structure, Speed of adjustment, Climate change, Paris Agreement, Balance sheet composition.

    JEL Classification: G21, G28, Q53, Q54.

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

No 118
2023-12-21

The Dynamics of Product and Labor Market Power: Evidence from Lithuania

  • Abstract

    This paper characterizes the power dynamics of firms in both product and labor markets in Lithuania between 2004 and 2018. We first show that both markets are not perfectly competitive, as both price markups and wage markdowns are far from unitary and homogeneous. Interestingly, we unveil that the Dynamics of these margins followed different patterns. On the one hand, both the dispersijon and the economy-wide markup have increased, indicative of an increase in product market power. On the other hand, we document a decline in monopsony power, as both the heterogeneity and the aggregate level of markdowns have declined. Altogether, our results underline the importance of jointly analyzing product and labor markets when assessing firms’ market power.

    Keywords: Firm heterogeneity, Monopoly, Markups, Monopsony, Markdowns.

    JEL Classification: D4, E2, J3, L1.

No 117
2023-12-06

Labor Market Competition and Inequality

  • Abstract

    Does competition in the labor market affect wage inequality? Standard textbook monopsony models predict that lower employer labor market power reduces wage dispersion. We test this hypothesis using Social Security data from Lithuania. We first fit a two-way fixed effects model to quantify the contribution of worker and firm heterogeneity to wage dispersion and document that the compression of dispersion in firm fixed effects has been the main source of the decline in inequality over the past 20 years. Using a theory-based relationship, we then leverage variation across sectors and over time to show that a 10 percentage point increase in labor market competition leads to a 0.7 percentage point reduction in the variance of firm-specific wage components. A counterfactual exercise using our preferred estimates suggests that the increase in labor market competition can explain at least 15 percent of the observed decline in overall wage inequality.


    Keywords: Wage inequality, Firm heterogeneity, Monopsony, Labor supply elasticity.
    JEL Classification: J31, J42, O15.

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