Pierre-Alain Pionnier
OECD Economic Surveys: Lithuania 2025
Abstract
After a strong post-pandemic recovery, high inflation and waning external demand weighed on economic activity in 2022-23, but growth has picked up in 2024 and is expected to continue gathering momentum over 2025-26. While inflation was largely driven by external factors, strong wage growth exacerbated by labour shortages also fuelled it and has weighed on cost competitiveness. A significant fiscal adjustment will be needed to face upcoming spending pressures related to ageing. This will require increasing the efficiency of public spending, broadening the tax base and strengthening public revenues by encouraging formal economic activity.
1.1.1. Economic activity slowed down in 2023 before rebounding in 2024
After a strong post-pandemic recovery, Russia’s war of aggression against Ukraine has contributed to higher inflation, elevated uncertainty and lower growth. As a result, GDP growth slowed down to 2.5% in 2022 and 0.3% in 2023 amid a sharp decline in inventories. High inflation has weighed on real wages and private consumption declined almost continuously from mid-2022 until mid-2023. This only reversed course in the third quarter of 2023, driven by a pick-up in real wages and consumer confidence. Investment supported economic activity in 2023 but declined in 2024, due to low capacity utilisation and subdued business confidence. Slowing growth in Lithuania’s main trading partners led to a decline in exports in 2023 before the situation started to improve in early 2024. The contribution of net exports to GDP growth remained positive in 2023, but only because decreasing domestic activity led to a simultaneous decline in imports. Nevertheless, the decline in energy prices improved the trade balance from early 2023 onwards (Figure 1.1).
Source: Panels A, B and D: Eurostat, Panel C: European Commission (Joint Harmonised EU Programme of Business and Consumer Surveys)
1.1.2. Despite low growth, the labour market has held up well
The inflow of migrants following Russia’s war of aggression against Ukraine in 2022 led to a 4% increase in the size of the labour force compared to 2021. Due to the successful integration of migrants in the labour market (Chapter 4), the employment rate has remained historically high (Figure 1.2, Panel A). While immigration helped to alleviate labour shortages, the labour market is tight (Figure 1.2, Panel B), and this contributes to strong wage growth (see below).
Note: In Panel A, the labour force count and the employment rate refer to workers aged 15-64. In Panel B, the vacancy rate is defined as the ratio between the number of job vacancies and the number of unemployed workers.
Source: OECD Database on Labour Statistics; Statistics Lithuania (job vacancies)
1.2.1. Domestic factors contributed to higher inflation
Headline inflation in Lithuania peaked at 22.5% in September 2022, using the HICP definition. This marked one of the highest levels in the euro area, before decreasing steadily to 0.1% in October 2024. The initial increase and the subsequent decrease in inflation have largely mirrored developments in energy and food prices, as Lithuanian households have a higher share of energy and food in their consumption basket (34%) than their euro area peers (26%) (Figure 1.3). Most recently, headline inflation ticked up to 3.4% in January 2025, due to diminishing base effects on energy prices and recent increases in excise duties on energy (Chapter 3).
When it peaked at 12.7% in November 2022, core inflation, which abstracts from the more volatile items, was the highest in the euro area. Beyond their direct effect on household consumption, energy and food price shocks increased input prices for firms, pushing up producer price inflation. Nevertheless, such input-output linkages can only explain part of the recent inflation developments in Lithuania and domestic price developments also added to price pressures (Coutinho et al., 2023, pp. 19-23[1]). While unit profits increased, strong wage growth added to core inflation, as real wages increased more in Lithuania than in other OECD countries (Figure 1.4, Panel A). This translated into higher unit labour costs (ULCs), feeding back into higher domestic prices. ULC growth explains around two thirds of the cumulated increase in the GDP deflator between 2019 and 2023, while unit profit growth accounts for slightly less than one third, and unit taxes for the rest (Figure 1.4, Panel B).
Note: Panel A features national CPI inflation and its underlying contributions. Panels B focuses on HICP inflation because it is the only inflation measure that is available for the euro area as a whole. Differences between CPI and HICP inflation are marginal for Lithuania.
Source: OECD Database on Consumer Prices
Note: In Panel A, real wages refer to gross wages and salaries (D11) in quarterly national accounts, divided by the number of employees and the national CPI. In Panel B, the evolution of the GDP deflator captures domestic price developments, above and beyond imported inflation.
Source: OECD Databases on Quarterly National Accounts, Productivity, and Consumer Prices; OECD calculations
While the minimum wage was raised by 15.1% in 2023 and by another 10.0% in 2024, its level has become less binding over time and has declined relative to average wages since 2016. Recent minimum wage hikes do not seem to have added much to existing wage pressures (Figure 1.5, Panel A). At the same time, possible adverse effects from the minimum wage on competitiveness cannot be ruled out in the future. Against this background, the tripartite commission in charge of setting the minimum wage should account for labour productivity developments and ensure that future upward adjustments do not jeopardise competitiveness.
While more research would be needed to account for a possibly stronger response in the recent period, preliminary evidence suggests that the energy price shock is unlikely to have triggered the strong observed wage response by itself (Bogužas et al., 2024[2]). Labour shortages may have contributed to wage growth more significantly, as wages have grown more in sectors with more unfilled positions (Figure 1.5, Panel B). On-going demographic changes are likely to aggravate these labour market tensions, suggesting a need to both facilitate the integration of foreign workers and increase the employability of older-age workers (Chapter 4).
Note: In Panel A, the ratio of the minimum to the average wage is calculated by dividing the minimum wage for 40 hours of work by the average wage of full-time employees working in the business sector and enterprises with 10+ employees. The average wage excludes irregular payments such as exceptional bonuses and allowances. Considering all (full-time and part-time) employees in the denominator, as Eurostat does, leads to a minimum-to-average wage ratio of 45.4% in 2023, vs. 39.2% when focusing on full-time employees. Both measures tend to move in parallel and have declined over the last years.
In Panel B, wages refer to gross wages and salaries (D11) divided by the number of employees in quarterly national accounts. The vacancy rate is defined as the ratio between the number of job vacancies and the number of employed workers in each sector. Recruitment difficulties, measured by the vacancy rate, explain 20% of the variance in wage growth across sectors between 2020Q3 and 2024Q3.
Source: Panel A: OECD Database on Labour Statistics; Panel B: OECD Database on Quarterly National Accounts (wages and employees), Statistics Lithuania (job vacancies); OECD calculations
While lower than in the EU and the other Baltic countries, the gender wage gap is above 10% and has not decreased over the last decade (Figure 1.6, Panel A). Nevertheless, women are as likely as men to be employed (Figure 1.6, Panel B), and they are not overrepresented in part-time jobs, contrary to what happens in many other OECD countries. Econometric analysis shows that the wage gap is not related to composition effects but remains after controlling for educational attainment and work experience. Moreover, it appears early in professional life and does not significantly increase over time, indicating that it is more related to discrimination between men and women than to labour market choices related to childbearing (Ciminelli, Schwellnus and Stadler, 2021[3]). In order to address this issue, Lithuania introduced in 2017 annual wage reporting requirements for all companies with more than 20 employees. As of 2021, the Social Security Fund has started to publish company-level gender wage gaps based on administrative data on all companies with more than 8 employees, thus ensuring a large coverage of firms and consistent reporting (OECD, 2021, pp. 59-60[4]). It is now time to launch a statistical evaluation of this measure. If it proves insufficient, Lithuania could consider imposing fines and mandating equal pay audits in companies where wage gaps exceed a given threshold. Equal pay audits already exist in 9 OECD countries. They are conducted by employers or external auditors to identify the reasons underlying wage gaps and recommend targeted actions. The transposition into Lithuanian Law of the 2023 EU Directive “to strengthen the application of the principle of equal pay for equal work […] between men and women through pay transparency and enforcement mechanisms”, which is due by June 2026, will provide an opportunity to implement this recommendation.
Note: Panel A: The gender wage gap is the relative difference between the average wage of men and women, without controlling for any composition effect. Panel B: The gender employment gap is the difference in employment rate between men and women.
Source: Eurostat Database on the European Pillar of Social Rights
1.2.2. Cost-competitiveness has weakened in recent years
While the trading partners of the three Baltic countries and the external demand addressed to them is similar, Lithuania’s exports have largely outpaced this external demand over the last decade, as well as Estonia’s and Latvia’s exports. Lithuania’s cost competitiveness has probably contributed to this outcome (Figure 1.7).
Nevertheless, strong wage growth outpacing productivity growth has eroded Lithuania’s cost competitiveness in recent years. Stronger productivity growth in Lithuania than in peer countries (Chapter 2) is one of the factors contributing to stronger wage growth, but relative unit labour costs (ULCs) in the manufacturing and tradable sectors have increased significantly during the high-inflation period. ULCs in Lithuania’s tradable sector remain lower than in Estonia and Latvia, but they have increased more significantly since the end of 2019. While they were around 20% lower than in Germany in mid-2024, this differential was twice as large just before the COVID-19 pandemic (Figure 1.7).
As an economy develops, productivity convergence tends to lift wages in the tradable sector. This wage growth then spills over to the rest of the economy, and both wages and prices tend to increase in the non-tradable sector. Nevertheless, when real wage growth outpaces productivity growth in the tradable sector, where prices tend to be set globally, cost competitiveness declines, which tends to damage the profitability and/or the export capacity of domestic firms.
Note: The above ULCs are relative ULCs compared to Germany, which is normalised to 100 each year. In Panel B, the tradable sector is defined as the aggregation of industries with a share of imports or exports in value added (VA) above 10%. This excludes construction (F), real estate (L), government services (O, P, Q), arts, entertainment and recreation (R), and other services (S, T, U). Therefore, the tradable sector includes manufacturing. Labour costs in the numerator are expressed in current euros, using the nominal exchange rate for currency conversions whenever needed. These labour costs include imputed labour costs for self-employed workers, assuming that self-employed workers have the same hourly labour cost as employees belonging to the same industry. VA in the denominator is expressed at constant 2017 prices. The conversion to comparable 2017 prices across countries is based on industry-level PPPs, aggregated to match the tradable sector definition using VA weights.
Source: (Inklaar, Marapin and Gräler, 2023[5]) for industry-level PPPs, OECD Database on Quarterly National Accounts, OECD calculations
Lithuania’s exports of goods and services declined in 2023, for the first time since 2014, amid declining foreign demand and export performance compared to foreign competitors (Figure 1.8, Panel A). Estonia and Latvia faced even larger declines in exports. Lithuania’s overall export decline in 2023 was related to goods, and this may be partly due to composition effects, as the products in which Lithuania specialises saw particularly strong declines in external demand, in particular timber and wood products used for construction. Nevertheless, this outcome is also related to deteriorating competitiveness (Figure 1.8, Panel B). This was particularly the case for agricultural and chemical products. Competitiveness captures everything that contributes to lower export growth for specific products and markets in Lithuania compared to foreign competitors. Part of the observed competitiveness decline in 2022-23 may be related to temporary factors such as lower crop yield and sanctions against specific firms. Nevertheless, reverting to wage growth in line with productivity developments would help to maintain Lithuania’s competitiveness in the longer term.
Note: This Figure does not consider reexports but focuses on exports of goods of domestic origin which are arguably more sensitive to domestic price developments. In Panel A, export performance is defined as the contribution to export growth that is not explained by overall import demand from third countries (i.e. foreign demand). In Panel B, the decomposition of export performance is based on a constant market share analysis, following the methodology described in (Bank of Lithuania, 2013[6]). The competitiveness effect captures the evolution of Lithuanian export market shares for individual products. Product and market effects capture the impact of export structure on export performance, i.e. to what extent Lithuania’s product and export market specialisation contribute to higher export growth than overall foreign demand.
Note: Due to data limitations, imports and exports of goods are recorded based on cross-border flows, while imports and exports of services are recorded based on the change of ownership between residents and non-residents.
Source: Bank of Lithuania (exports and imports of services), Statistics Lithuania (exports and imports of goods), OECD calculations
Following a rebound in 2024, GDP growth is projected to increase further by 3.1% in 2025 and 2.8% in 2026. While potential GDP growth is expected to decline amid slower labour and productivity growth, actual GDP growth in 2025-26 will partly close the negative output gap resulting from low growth in 2023. Sustained real wage gains, a resilient labour market with unemployment below its long-term average and increasing consumer confidence are expected to support a pickup in household consumption, especially in 2025. Investment is projected to pick up over 2025-26, supported by improving financial conditions. While early GDP estimates point to a strong decline in exports in the last quarter of 2024, quarterly export growth is expected to progressively resume over 2025-26, along with improving conditions in Lithuania’s main trading partners.
Note: 1: Contribution to changes in real GDP; 2: as a percentage of potential GDP; 3: as a percentage of household disposable income; 4: as a percentage of GDP.
Source: Statistics Lithuania, OECD. Cut-off date for the projection (2025-26): 3 March 2025.
Economic activity in the euro area is a key risk for the outlook, along with global commodity prices and geopolitical tensions. Lithuania’s energy security is rapidly improving, but geopolitical tensions could affect commodity prices and have a significant impact on the economy. Gas imports from Russia started to decline after a liquified natural gas (LNG) terminal on the Baltic Sea was opened in 2014. Lithuania also has its own oil refinery and oil terminal on the Baltic Sea and is connected to the EU electricity network. These facilities allowed Lithuania to stop all imports of oil, gas, and electricity from Russia in early 2022. Moreover, the electricity network of the Baltic countries has been successfully disconnected from the Russian network on February 8, 2025. Nevertheless, an unexpected increase in commodity prices triggered by geopolitical tensions could fuel inflation, monetary tightening and uncertainty in Lithuania, thereby derailing the on-going recovery. Geopolitical tensions also increase the risk of cyberattacks, which may affect the financial system and other digital services (Table 1.2).
1.4.1. The Lithuanian financial system has sound fundamentals
Lithuanian banks are well capitalised, all well above the minimum ratios of regulatory capital to risk-weighted assets imposed by the ECB and the Bank of Lithuania, and slightly above the OECD average (Bank of Lithuania, 2023, p. 9[9]) (Figure 1.10, Panel A). These high capital ratios are supported by strong bank profitability, which can be explained by the rising gap between lending and deposit rates in the recent period, and more structurally by the concentration of the Lithuanian banking sector. At 0.5%, the ratio of non-performing loans to gross loans is also well below the OECD average (Figure 1.10, Panel B) and has been continuously declining since the mid-2010s. The latest stress tests show that the Lithuanian banking sector as a whole would be resilient to an export-led contraction in economic activity, accompanied by a correction in the real-estate market. However, large banks are found to be more resilient than smaller institutions, which may require additional capital if this adverse shock materialises (Bank of Lithuania, 2024[10]).
Source: IMF Financial Soundness Indicators
1.4.2. The housing market requires vigilance
Despite the increase in interest rates triggered by ECB monetary policy tightening, credit disbursements remain robust (Figure 1.11), which may be related to the fact that credit standards in Lithuania did not tighten as much as in the euro area during 2022-23 (European Central Bank, 2024[11]). Moreover, the housing market only cooled down temporarily. While nominal house price growth declined from 22% per year in mid-2022 to 8% in end-2023, real house prices also decreased marginally in late 2022 and early 2023, but they have accelerated again since then (Figure 1.12, Panel A). Real house price growth in 2024Q3, at 9.1% per year, was one of the highest in the euro area. Housing overvaluation indicators suggest that the housing market is slightly overheating (Figure 1.12, Panel B).
Note: New loans to corporations and households at current prices have been deflated by the Lithuanian CPI (2024-M01 = 1). In Panel A, the volume of new loans to corporations is shown as a moving average over the last three months.
Source: Bank of Lithuania (interest rates), European Central Bank (loans), OECD calculations
Since 98% of mortgages in Lithuania have a variable interest rate, which is the highest share in the euro area, monetary policy tightening has immediately increased the debt servicing costs for households. In late 2023, indebted households in the first income quintile were allocating 45% of their income to mortgage payments, nearly 10 percentage points more than in mid-2022 (Figure 1.12, Panel C). Moreover, excess savings accumulated during the pandemic have fallen (Figure 1.12, Panel D). Nevertheless, no significant increase in non-performing mortgage loans has been observed so far and the gradual decline in interest rates will ease the financial burden on indebted households.
In this context, housing market risks should be closely monitored. While the Central Bank increased the overall countercyclical capital buffer to its pre-pandemic level of 1%, but maintained the 2% sectoral systemic risk buffer applicable to housing loans in October 2023 (Table 1.3), it should stand ready to increase the sectoral systemic risk buffer if needed. Moreover, specific action may be needed to relieve low-income households facing too high mortgage servicing costs.
Note: In Panel B, the house price overvaluation indicator is constructed as the median of six sub-indicators assessing the sustainability of house prices: the house-price-to-income ratio, the house-price-to-rent ratio, the HP-filtered nominal house price index, the HP-filtered real house price index, and two indicators based on models capturing the imbalance between fundamental and actual house prices. Vertical bars reflect the dispersion between minimum and maximum values of the six sub-indicators. The higher the overall indicator, the more overvalued is the housing market.
Source: Panel A: OECD Analytical House Price Database; Panels B, C: Bank of Lithuania; Panel D: OECD Database on Financial Accounts, Statistics Lithuania, OECD calculations
1.4.3. The expanding Fintech sector comes with opportunities and regulatory challenges
Lithuania has the ambition to strengthen its position as a financial technology (Fintech) hub in Europe by encouraging the reshoring and the development of Fintech firms (Government of Lithuania, 2023[13]). These efforts are in line with EU objectives, in particular with the Digital Finance Strategy to support the development of digital finance that the European Commission issued in the wake of the COVID-19 pandemic (European Commission, 2020[14]).
By allowing financial institutions to identify creditworthy borrowers faster and reducing financial intermediation costs, Fintech has the potential to mitigate the financial constraints experienced by households and firms, thereby fostering financial inclusion and stimulating innovation and growth (Chapter 2). Nevertheless, Fintech also comes with potential financial stability challenges, due to the fact that digital and traditional banks have different business models, and that the Fintech sector does not only include banks but a variety of financial intermediaries (Box 1.1).
Fintech, or financial technology, refers to the use of technology to compete with traditional financial methods in the delivery of financial services. From 55 in 2014, the number of Fintech firms in Lithuania increased to 276 in 2023 (Figure 1.13). 7400 employees, or 0.5% of the Lithuanian labour force, work in those firms. 33% of them provide payment services, 22% provide lending or digital banking services, and 13% focus on cryptocurrency and blockchain technologies. The others are engaged in financial software development, big data analytics, or insurance technology (Insurtech) (Invest Lithuania, 2024[15]).
Source: (Invest Lithuania, 2024[15])
Fintech banks and non-bank financial intermediaries
The Lithuanian banking sector has expanded rapidly over the last years, with the number of banks increasing from 12 in 2018 to 19 in 2022 (Bank of Lithuania, 2023[16]). The new banks that recently registered in Lithuania mostly belong to the Fintech sector. They differ from traditional banks in the way they collect funds and interact with customers, and some specialise in payment services. Fintech banks in Lithuania mostly collect deposits from non-resident customers, via digital platforms. While in 2022 the share of non-resident deposits in total deposits was 6% for traditional banks, it was 97% for Fintech banks (Bank of Lithuania, 2023[16]).
Due to the inflow of foreign funds, deposits in Lithuanian banks more than doubled between 2016 and 2022 and represented 39% of Lithuania’s GDP in 2022. Lithuania’s Deposit Guarantee Scheme (DGS) guarantees the deposits of all Lithuanian banks up to EUR 100,000 per depositor, regardless of their country of residence. Its financial means have increased over time (Figure 1.14). In 2023, the Lithuanian DGS held slightly more than 1% of insured deposits, which was above the 0.8% target set by the EU DGS Directive (Figure 1.14). The 2016 Law on Insurance of Deposits and Liabilities to Investors sets as an objective that DGS assets should reach 2% of insured deposits by 2038, which would be one of the highest levels in the EU. Moreover, the Law on Insurance of deposits and liabilities to investors allows the use of the liquid assets of a failed credit institution to compensate depositors, even before resorting to the DGS. The four largest banks, which hold around 93% of insured deposits, have designed resolution strategies in case of failure, thus making the use of DGS funds less likely.
Despite all preventive actions that have been put in place, the national budget would have to be mobilised if ever DGS assets proved insufficient to compensate the depositors of a failed bank. Given the small size of the Lithuanian economy and the large share of non-resident depositors in Fintech banks, the target level of the Lithuanian DGS should be assessed at regular time intervals.
On the asset side of their balance sheet, digital banks in Lithuania have a less diversified and thus riskier loan portfolio than traditional banks. While traditional banks have a balanced allocation of assets between consumer, housing and corporate loans, digital banks tend to specialise in either consumer or corporate loans, but these specificities are accounted for in the stress tests conducted by the Bank of Lithuania (Bank of Lithuania, 2023[16]). A key supervision challenge is related to the fact that most firms in the Fintech sector are not considered banks but non-bank financial intermediaries (NBFIs). NBFIs are not subject to the same license requirements and supervision as banks. For example, only banks are subject to the regular stress tests conducted by the European Banking Authority and the European Central Bank (European Central Bank, 2023[18]). Nevertheless, linkages with the NBFI sector expose banks to liquidity, market and credit risks, because part of bank assets are loans to NBFIs and because NBFIs contribute to the financing of banks (Franceschi et al., 2023[19]). Preliminary empirical evidence also points to financial stability risks related to digital lending (Cevik, 2023[20]).
In addition to usual macro-financial risks, Fintech firms are subject to specific risks that should be taken into account by financial regulators and stress tests. Such risks include cybersecurity risks, operational risks from third-party service providers such as cloud computing service providers, and specific credit and liquidity risks, e.g. due to the opacity of some big data frameworks that could lead to excessive risk taking and excess volatility in periods of financial stress (Financial Stability Board, 2017[21]).
Decentralised finance (DeFi) that Lithuania aims to develop as part of its Fintech strategy is a case in point. DeFi refers to financial applications based on blockchains, with limited or no involvement of centralised intermediaries. DeFi lending platforms receive crypto assets as deposits and lend them out to borrowers who meet certain collateral criteria. Volatile collateral is typically used to borrow stable cryptocurrencies called stablecoins, which generates credit risk. Moreover, the liquidity origin of DeFi platforms tends to be highly concentrated, which increases liquidity risk during periods of market stress (International Monetary Fund, 2022[22]). While such risks also exist in the traditional banking sector, they may be more acute in decentralised finance and require specific financial supervision.
In a context where the Lithuanian Fintech sector has rapidly expanded, the Bank of Lithuania, together with the Ministry of Finance and other competent authorities, is continuously improving the monitoring and risk assessment of the Fintech sector. The links between the Fintech sector and other financial market participants, and the resulting risks for banks and other financial institutions, are continuously monitored and results are made available to the public.
The Bank of Lithuania should continue to take a leading role in research activities around Fintech and financial stability, and in the evolution of financial supervision in the euro area to encompass all Fintech activities. Fintech activities have the ability to scale up rapidly and financial supervision should develop at the same pace. Lithuania’s Fintech Strategy rightly mentions cybersecurity risks and risks related to money laundering and the financing of terrorism (Government of Lithuania, 2023[13]), but potential financial stability risks related to Fintech should also be kept in mind.
Money laundering and financing of terrorism (ML/FT) risks
The emergence of a large Fintech sector poses ML/FT risks because the origin of funds raised through digital platforms may be difficult to trace. In recent years, the Central Bank has significantly increased its ML/FT supervisory resources and the related number of controls, and strengthened requirements for getting access to the Single Euro Payments Area (SEPA) infrastructure (International Monetary Fund, 2024, pp. 12-13[23]). These are all steps in the right direction. The government’s intention to extend the activities of the Centre of Excellence in Anti-Money Laundering to Fintech companies is also welcome (Government of Lithuania, 2023[13]).
MONEYVAL’s latest evaluation of the compliance of Lithuania’s overall financial sector with international ML/FT standards acknowledges significant progress in recent years. While there were 8 areas out of 40 for which Lithuania was considered only partly compliant in 2018, only 4 remained in 2023 (MONEYVAL, 2023[24]). Efforts should continue to reach compliance in all areas as soon as possible.
1.5.1. Public finances have been carefully managed over the last decade
After the COVID-19 pandemic and the related sharp increase in the fiscal deficit, the government removed the strong support measures as early as 2021 (Figure 1.15). As a result of this quick fiscal stance reversal and the 2021 rebound in GDP growth, public debt started to decline immediately after the pandemic, after having increased by 10 percentage points of GDP in 2020. In 2023, Lithuania’s public debt as a share of GDP was one of the lowest in the OECD (Figure 1.16). Many previous fiscal policy recommendations formulated in OECD Economic Surveys have been implemented (Table 1.4).
The fiscal stance became more restrictive from 2021 to 2023 but then reversed course in 2024. More could be done to prepare for future spending needs (see below). The main factors leading to a more accommodative fiscal stance over 2024-26 are related to pension benefit increases and public wage growth. The significant increase in pensions is largely related to the new indexation rule that was introduced in 2022 to ensure that old-age poverty does not increase above 25% and that the average old-age pension does not fall below 50% of the average net salary (Chapter 4). Therefore, strong wage growth now has a direct impact on pension benefits. While public wage growth is in line with private wage growth, care should be taken to avoid a situation where public-sector pay would add to existing wage pressures. Examining public wages on a case-by-case basis and considering that the public sector is paying a wage premium compared to the private sector would seem like a prudent strategy (see below).
Note: Except when tax innovations are introduced, government revenues tend to track GDP very closely. By contrast, in absence of spending innovations, the level of government expenditure tends to be stable over the business cycle. Since government expenditure represents around 35% of GDP in Lithuania, the government expenditure-to-GDP ratio mechanically decreases by 0.35 percentage point when GDP increases by 1%. This explains the difference between the headline and the cyclically-adjusted government balance. Tax and spending innovations are reflected to the same extent in both ratios. All details of the OECD methodology are explained in (Price, Dang and Botev, 2015[25]).
Source: Statistics Lithuania, OECD. Cut-off date for the projection (2025-26): 3 March 2025.
Source: Statistics Lithuania, OECD. Cut-off date for the projection (2025-26): 3 March 2025.
1.5.2. In the longer term, rising spending pressures will require building more fiscal space
Looking ahead, Lithuania will need to create additional fiscal space to prepare for the upcoming increase in ageing-related costs in a context where the population is both ageing and shrinking. According to the latest projections of the European Ageing Working Group, ageing-related costs net of social contributions are likely to increase by 3.9% of GDP between 2023 and 2050 (European Commission, 2024[26]). Considering that old-age poverty is one of the highest in the OECD and that life expectancy is low, political pressures for additional pension spending are likely to increase. Against this background, there is limited scope to cut pensions and further increase the retirement age once it will have reached 65 by 2026, at least in the short term (see Chapter 4 for a discussion of this issue and a description of the Lithuanian pension system). In order to avoid relying on public debt to finance the additional ageing-related costs, an additional fiscal space of 3 percentage points of GDP per year would need to be created by 2028 (Figure 1.17, red and blue lines). This is the purpose of measures 1, 3 and 4 in Table 1.5, which will be discussed in the next section.
Contrary to ageing-related costs, the financing of investments in renewable energy sources may justify an increase in public debt, subject to the limits imposed by the EU fiscal framework. This is because this investment will benefit future generations by mitigating global warming and improving Lithuania’s energy security, thus justifying a transfer of some of the related costs to future generations in the form of public debt. The required capital expenditure has been estimated at around 2% of GDP per year until 2050 (DNV EPSO-G, 2023[27]) (Chapter 3). EU funds are expected to contribute to the investment in renewables by around 0.5% of GDP over 2024-26 (Chapter 3). Nevertheless, most of these funds are temporary because they are related to the EU Recovery and Resilience Facility (RRF), which will end in 2026. It would be prudent to anticipate the need to replace them with domestic funds after 2026. Domestic funds allocated to public investment could be increased by around 0.5% of GDP per year while respecting the EU fiscal framework and keeping public debt just below 60% of GDP by 2060 (Figure 1.17, red line). A larger budget contribution to renewable energy investments would require creating further fiscal space.
In light of current geopolitical tensions, the government increased defence spending to 3% of GDP in the 2025 budget, up from 2.5% in 2023. The required financing is covered by an increase in the standard and reduced corporate income tax rates of 1 percentage point, additional excise duties, a contribution of 10% on insurance contracts, and an extension of the Solidarity Contribution levied on banks until 2026 (Ministry of Finance of Lithuania, 2024[28]). From 2026 onwards, other fiscal resources will need to increase by 0.1 percentage point of GDP to compensate for the phasing out of the exceptional levy on banks. In January 2025, the State Defence Council agreed to raise defence spending to 5-6% of GDP annually over 2026-30. Since this objective has not yet been endorsed by Parliament, it is not considered in the debt sustainability analysis below (Figure 1.17). Nevertheless, it is clear that higher defence spending will require creating additional fiscal space, especially if extended beyond 2030.
Government debt (Maastricht definition), % of GDP
Note: Ageing-related costs cover public expenditure related to pensions, healthcare and long-term care. Pension costs are net of social contributions. Cost estimates are those of the baseline scenario in the 2024 Ageing Report of the European Commission. The green transition costs considered here only include the financing of capital expenditure in renewable energy sources and are limited to 0.5% of GDP per year from 2028 to 2050, to compensate for the expected decline in EU financing (mainly RRF).
Source: (European Commission, 2024[26]), OECD calculations
The structural fiscal balance improvement of 3 percentage points (pp) of GDP to finance increasing ageing-related costs (Figure 1.17) would be achieved by public spending efficiency improvements, increases in property taxes, and a reduction in the VAT compliance gap, with the objective that each of these measures generates 1 pp of GDP in additional revenues or savings. The recommended reduction in social security contributions (SSC) and/or personal income tax (PIT) for low-income workers to incentivise formal work would be compensated by an increase in PIT progressivity to ensure fiscal neutrality.
In addition, Table 1.5 considers an increase in public investment of 0.5 pp of GDP. Allocating this investment to the financing of renewable energy sources or to defence would have the same impact on public debt. A larger investment would require raising additional fiscal revenues or reducing other expenditures.
Source: OECD estimates
1.5.3. Streamlining Lithuania’s fiscal framework and aligning it with the new EU fiscal rules
While Lithuania’s fiscal framework (Box 1.3) has contributed to the prudent management of public finances over the last decade, it includes so many exceptions that with hindsight, it looks complex. In other countries as well, flexibility in fiscal frameworks has often been reached at the cost of simplicity and transparency (Eyraud et al., 2018[29]). Moreover, the reason why Lithuania’s fiscal framework includes both a structural surplus rule and a rule limiting the increase in public expenditure is unclear and these two rules may conflict with each other. For example, under the structural surplus rule, government expenditure may increase as long as revenues increase in parallel to ensure that the structural deficit does not exceed the medium-term objective set by Parliament. Nevertheless, this may be inconsistent with the expenditure growth limiting rule.
Lithuania’s fiscal framework is set out in the 2014 Constitutional Law on the Implementation of the Fiscal Treaty, but the corresponding rules have been temporarily suspended since March 2020 under the exceptional circumstances prevailing since the pandemic and the war in Ukraine. The National Audit Office, acting as an Independent Fiscal Institution, expects those rules to apply again from 2025.
General Government (GG) surplus rule: There should be no structural GG deficit or it should be declining when the output gap is positive. When the output gap is negative, it should not exceed the medium-term objective set by Parliament. For 2023-25, this objective is 1% of GDP.
GG expenditure growth limiting rule: The nominal growth of GG expenditure should not exceed half of the 10-year average of potential nominal GDP growth. This rule does not apply in the following cases:
Slow convergence: Lithuania’s nominal GDP growth is below the average EU nominal GDP growth over the last 5 years, plus 2 percentage points (pp).
Expected GG fiscal balance improvement by at least 1 pp of GDP.
Medium-term budget surplus: The average GG balance over the last 5 years is positive.
Cyclical downturn: Expected GDP growth is below potential GDP growth.
Budget revision: The rule does not apply to budget revisions if they do not deteriorate the GG balance compared to the initial budget.
Specific rules apply for different GG subsectors:
The National Health Insurance Fund (NHIF) and the municipalities with a budget exceeding 0.3% of GDP should always have a structurally balanced budget.
The State Social Insurance Fund (SSIF) may only increase its structural deficit when the output gap is negative.
Municipalities with a budget below 0.3% of GDP should not have any headline deficit when the output gap is positive.
Source: (National Audit Office, 2024[30]), Government of Lithuania
Lithuania’s fiscal framework has been suspended since 2020 and the revision of EU fiscal rules in April 2024 offers an opportunity to review and streamline it. From 2024 onwards, the reference fiscal trajectory provided by the European Commission is based on a net expenditure indicator defined as government expenditure, net of discretionary revenue measures, interest expenditure, cyclical unemployment expenditure, national expenditure to co-finance EU programmes, and expenditure on EU programmes fully matched by revenue from EU funds (European Council, 2024[31]).
Focusing on net expenditure and a debt anchor would make Lithuania’s fiscal framework easier to understand, simplify the preparation of medium-term fiscal structural plans and budget discussions with the EU, and allow raising revenues to meet inevitable spending needs. In order to avoid that discretionary revenues are systematically raised by the same extent as emerging spending needs, which would lead to a continuous increase in the fiscal pressure, the National Audit Office should play an active role in assessing spending efficiency and identifying possible savings. Net expenditures would be easier to measure than the structural fiscal balance because they would not require estimates of the output gap or of cyclical reactions of expenditures and revenues to the business cycle, except for unemployment benefits. Such a change could thus increase the transparency of the budgetary process. In the future, the medium-term objective set by Parliament could focus on such an indicator. Finally, acknowledging that the debt anchor is 60% of GDP would be consistent with EU rules and provide some welcome flexibility to finance upcoming investment expenditures related to energy security and the green transition, or defence (see above and Figure 1.17).
1.5.4. Increasing the efficiency of public spending
While higher taxes may be necessary to finance future expenditures, spending efficiency improvements also have a role to play to improve the structural fiscal balance. For example, Lithuania has a large public sector compared to its population and this sector is paying a wage premium of around 10% compared to the private sector, controlling for worker characteristics (Figure 1.18). Nevertheless, a large share of the population is dissatisfied with public services (Figure 1.19). Given current average labour costs in the public sector, the larger number of public employees per inhabitant than the OECD average represents an expenditure of 1.9% of GDP.
Note: In Panel B, the public sector wage premium is estimated in a regression controlling for gender, age, occupation, skill level and other observed characteristics of workers, as explained in (World Bank, 2022, pp. 34-35[32]).
Source: Panel A: OECD Databases on National Accounts and Population; Panel B: World Bank, Worldwide Bureaucracy Indicators
Demographic change severely limits the scope for reducing pension expenditures (Chapter 4), but it does provide a unique opportunity to review the geographical organisation of public services and the type of services to be provided to an ageing population. Education and health services, which altogether represent close to 30% of government expenditure and have a strong territorial component, are particularly concerned by the on-going demographic change. Even though the number of local hospitals has been significantly reduced since independence, the public healthcare sector is one of those public services which could be further rationalised to reduce costs and increase service quality (Chapter 4). More generally, resource-sharing between municipalities is key to maintain local public services at an affordable cost. For education, this could mean developing school clusters and joint transport solutions between municipalities, as well as relying more on digital education (OECD, 2022[33]).
Spending reviews have the potential to increase the efficiency of public spending because they allow taking strategic decisions on the organisation of public services while avoiding blind and uniform expenditure cuts across the board. Lithuania has recently finalised a first major review of public spending on social protection, environment and agriculture and used it for the preparation of the 2025-27 medium-term budget. From 2025 onwards, it intends to rely on spending reviews more systematically. International experience shows that the impact of spending reviews depends on how they are organised. Clear objectives and scope such as a given spending reduction in a specific area must be announced from the outset. Having a clear governance structure with strong political support is helpful, often led by the Ministry of Finance using specialised resources dedicated to spending reviews, and line ministries involved at all stages. To increase their impact on fiscal policy, spending reviews should also be integrated in the annual or medium-term budget process. Their recommendations should be clear and directly actionable, publicly available and their implementation should be monitored (Tryggvadottir, 2022[34]).
Share of population that is satisfied with public services (2022, %)
Source: OECD Government at a Glance (2023[35])
1.5.5. Broadening the tax base
Lithuania’s fiscal revenues represented 32.6% of GDP in 2023, which is below most OECD and neighbouring countries except Latvia (Figure 1.20, Panel A). While the priority should be to enhance the efficiency of existing spending, there may also be scope for the revenue side of public accounts to contribute to the financing of increasing ageing-related expenditure. One case in point may be property taxes, including recurrent taxes on immovable property, other recurrent taxes on wealth, and inheritance and gift taxes. These are largely underused in Lithuania, as they only generated 0.3% of GDP in tax revenues in 2023, compared to 1.7% on average in other OECD countries (Figure 1.20, Panel B). Moreover, they are among the least detrimental taxes to economic growth (Arnold et al., 2011[36]). For example, distortive effects of inheritance and gift taxes on investment behaviour and work efforts of wealthy taxpayers have been found to be much smaller than labour and capital income taxes, and the effect on the labour supply of their heirs is significantly positive (OECD, 2021[37]) (Guvenen et al., 2023[38]). Beyond generating tax revenues, immovable property taxes may also help to shift some investment out of housing into higher-return economic activity (Arnold et al., 2011[36]).
An amendment to the Law on Immovable Property Tax that is currently under discussion in Parliament proposes to reduce current exemptions, transfer non-commercial real-estate tax revenues to municipalities, and let municipalities decide on local tax rates within a wide range (Table 1.4). Nevertheless, it is estimated that two thirds of main residence owners would remain exempted and that the related tax revenues would increase by at most 0.1% of GDP. Beyond any increase in tax rates, broadening the tax base may thus contribute to increasing recurrent tax revenues on immovable property.
Note: Property taxes include recurrent taxes on immovable property, other recurrent taxes on wealth, inheritance and gift taxes, taxes on financial and capital transactions, and non-recurrent property taxes.
Source: OECD Database on Revenue Statistics
1.5.6. Strengthening public revenues by encouraging formal activity
Shadow economy activities are partly or completely untaxed. Such activities decrease public revenues and may result in suboptimal provision of public goods or insufficient financing of social policies, which is especially problematic in the present context of rising spending pressures.
Measuring the shadow economy is challenging (Box 1.4) but different measures agree that may be in the range of 20 to 25% of GDP in Lithuania, well above the OECD average and at around the same level as in Estonia and Latvia (Figure 1.21). Most uncertainty related to the trend evolution of the shadow economy in Lithuania. While the indirect measurement method underlying Figure 1.21 shows a decline over time, a direct measurement method based on interviews of company managers suggests an increase, especially in the last few years (Sauka and Putniņš, 2023[39]).
Actions that the government could take to reduce the size of the shadow economy include strengthening controls and restricting the use of cash, making formal work pay, and increasing trust in public institutions to encourage citizens to pay the taxes they are subject to (Schneider and Asllani, 2022[40]). Only the first two actions will be described below. As increasing trust in public institutions is closely connected to improvements in the anti-corruption and public integrity framework, this issue will be addressed in Chapter 2.
Size of the shadow economy (2022, % of GDP)
Note: The above shadow economy estimates are based on a MIMIC approach (Box 1.4) The OECD average is an unweighted average of 32 OECD countries for which data is provided by (Schneider and Asllani, 2022[40]). The official GDP that is used in the denominator captures the “non-observed economy” to some extent (UN, 2010[41]), but estimation methods differ across countries. The Lithuanian State Data Agency estimates the non-observed economy to be around 13% of GDP, but results based on the same methodology are not available for other OECD countries.
The term “shadow economy” refers to the production of goods and services that is deliberately concealed from public authorities. It may also be called “informal”, “non-observed” or “unreported economy”. By nature, the shadow economy is difficult to measure as workers and firms engaging in it try to remain undetected. Available measurement strategies can be divided into indirect and direct methods:
Some indirect methods rely on single indicators which are supposed to capture the evolution of the actual but unobserved GDP, including both observed and shadow economies. Commonly used indicators include transactions in cash or electricity consumption. Two main limitations of these methods are the assumption that the chosen indicator is comprehensive, and the need to assume that actual GDP is known in a given year, which allows to calculate the size of the shadow economy in this year as the difference between actual and official GDP.
Other indirect methods, known as Multiple Indicator Multiple Cause (MIMIC) methods, treat the size of the shadow economy as an unobserved variable and relate it to its causes (e.g. tax and regulatory burden) and consequences (e.g. labour force participation reported in household surveys). A weakness of these methods is the need to calibrate the model based on external measures of the shadow economy in some countries and periods. Their main advantage is that they can be easily replicated across countries once model parameters have been estimated.
Direct methods rely on tax audits and surveys. While costly and imperfect, e.g. because surveys face the risk of underestimating the size of the shadow economy due to incomplete or untruthful responses, these methods provide useful information to cross-check the results of indirect methods and additional information on attitudes and perceptions by individuals, which may be useful to better understand the reasons why some economic activities are hidden. (Sauka and Putniņš, 2023[39]) rely on interviews with company owners/managers and provide shadow economy estimates for the three Baltic countries for every year since 2009.
Further restricting the use of cash, digitalising VAT collection and strengthening controls
Lithuania’s standard VAT rate is 21%, close to the EU average. For a given standard VAT rate, revenues can be curtailed by both imperfect compliance with existing rules and by exemptions and reduced rates that lower the amount of taxes due. While the VAT compliance gap, i.e. the difference between the expected VAT revenue given current rates and exemptions and the amount actually collected, has been significantly reduced over the last decade, it remains one of the highest in the EU. It is also much higher than in Estonia and Latvia despite similar standard VAT rates in the three Baltic countries (Figure 1.22, Panel A). Further reducing the VAT compliance gap should be considered a priority. Reducing it to the average value in Estonia and Latvia would increase tax revenues in Lithuania by around 1% of GDP.
By contrast, reduced VAT rates and exemptions in Lithuania are more limited than in most EU countries and reforms in this area do not provide significant opportunities for raising fiscal revenues. In 2021, the cost of reduced rates was only 3.5% of the theoretical VAT revenue that would accrue if the standard rate were applied to all goods and services. This difference is well below the EU average of 10.4% (European Commission, 2024[43]). One reduced rate that had been granted to the catering sector during the COVID-19 pandemic has been removed in early 2024, as recommended in the previous Economic Survey (OECD, 2022[12]). Remaining VAT exemptions mostly concern public services and housing rents, as in most countries. In 2021, they represented 30.4% of the theoretical VAT revenue, below the EU average of 34.5%.
A first avenue to reduce the VAT compliance gap would be to reduce the use of cash in the economy and encourage the use of digital payments which are easier to track for the fiscal administration. Cash is the mode of payment for 60% of transactions in Lithuania. This was the largest share in the euro area in 2024 (Figure 1.22, Panel B). The obligation for employers to pay all salaries into employee bank accounts from January 2022 and the law limiting cash payments to EUR 5,000 from November 2022 were steps in the right direction. Evaluating their impact could provide useful insights for future policy efforts to further reduce VAT avoidance. For example, Lithuania could consider reducing the ceiling above which payments in cash are prohibited. Making digital payments mandatory for all payments to the administration and public services would also help to generalise this practice. This would foster the digitalisation of the economy (Sorbe et al., 2019[44]) and support the wider use of electronic transaction systems and digital finance, thus contributing to alleviate financial constraints (Chapter 2).
Note: Panel A: The VAT compliance gap is the overall difference between the expected VAT revenue and the amount actually collected. It is expressed as a percentage of the VAT Total Tax Liability (VTTL), which represents 9.7% of GDP in 2021 in Lithuania. Since reduced VAT rates are reflected in lower VTTL, the VAT compliance gap only reflects tax avoidance. For the EU, it is calculated as an unweighted country average.
Source: Panel A: (European Commission, 2024[43]); Panel B: (European Central Bank, 2024[45])
The rollout of an electronic IT system allowing taxpayers to submit accounting data and VAT invoices electronically started in 2016, while the deployment of electronic cash registers over 2023-25 will allow transmitting transaction data in real time to tax authorities. Such measures could be used more widely, as is already the case in Latvia, Hungary and Poland (Box 1.5). A key aspect is to collect individual transaction data, ideally with no threshold, instead of total sales and purchases over a given time frame, as is usually the case in traditional VAT forms. The systematic digital collection of individual transaction data in real time may then allow to chart connections between firms, cross-check the information provided by sellers and buyers, and apply efficient machine-learning algorithms to detect anomalies and fraud in networks (Alexopoulos et al., 2023[46]).
Lastly, Lithuania could combat tax fraud by fostering data exchange between the tax and social security administrations, as well as between tax authorities and financial institutions, especially digital financial intermediaries in the Fintech sector which can be used for tax evasion. In this context, the current plan to mandate crypto-asset service providers to share information on their clients with the tax administration should be implemented.
Latvia, Hungary and Poland have managed to significantly reduce their VAT gap over the last decade (Figure 1.22, Panel A), which can be related to several policies:
The obligation to submit detailed transaction data through an electronic declaration system. Hungary, Latvia and Poland started to introduce such obligation in the early 2010s and have made it more stringent over time. Since 2018, detailed reporting is mandatory for all transactions above €150 in Latvia. Poland has progressively extended such obligation to all VAT taxable persons. Since 2021, all invoices issued and received should be electronically provided in real time to tax authorities in Hungary.
The introduction of a VAT reverse charge mechanism for goods and services that are suspect of large VAT fraud. While it has been introduced in the EU to avoid that suppliers have to declare VAT in Member States where they are not established and thereby facilitate intra-EU trade, it can also be used domestically to prevent VAT fraud. Latvia and Hungary use it for IT and electronic equipment, selected agricultural crops, and precious metals. Lithuania uses it for several transactions at risk of large VAT fraud, including those relating to construction works, ferrous and non-ferrous waste, mobile phones, tablets and laptops.
Poland has established a specific IT system (STIR) granting access to companies’ bank accounts to tax authorities to support the detection of fictitious transactions and enable temporary account blockage in case of detected fraud.
Source: (European Commission, 2024[43])
Making formal work pay
While the employment rate of high-skilled workers in Lithuania is one of the highest in the OECD, there is room to increase it for medium- and low-skilled workers (Figure 1.23, Panel A). The comparatively lower employment rates for these skill categories when compared to best-performing OECD countries reflects both higher inactivity and unemployment in Lithuania, hence a mix of labour supply and labour demand (Figure 1.23, Panel B).
While informal employment is partly captured in official employment statistics, some people that are officially registered as unemployed or inactive may also engage in hidden, informal activities. For example, recent survey evidence reveals that around two thirds of unemployed people in Lithuania work in the informal economy at some point during their unemployment spell (Gasparėnienė, Remeikienė and Williams, 2022[47]). Financial work incentives can encourage both informal workers, wherever they are recorded in official statistics, to move into formal employment, and truly unemployed or inactive people to accept formal job offers. Therefore, financial work incentives can contribute to the fight against informal economic activity, but their benefits extend beyond that.
Note: Panel A: In 2021, the employment rates of workers with below-upper-secondary, upper-secondary, and tertiary education in Lithuania were 57.8%, 73.7%, and 89.8%, respectively, as shown by the first histogram on the left. This compares with 71.5%, 84.0% and 90.8% in best OECD performers. Note that the later statistics do not correspond to a single OECD country.
Source: OECD Education at a Glance (OECD, 2022[48])
In theory, financial incentives to boost employment may concern social benefits received as well as taxes paid. In practice, given the high poverty rate that unemployed people are facing in Lithuania, there is hardly any room to increase financial work incentives by limiting unemployment benefits. Indeed, Lithuanian workers earning around the minimum wage when they are employed receive unemployment benefits that are already close to the poverty line at the beginning of an unemployment spell, even in the likely event where they have worked long enough to be entitled to full unemployment benefits (Figure 1.24). The situation further deteriorates over the unemployment spell as unemployment benefits decrease over time and are limited to 9 months. As a result, unemployed people face a poverty rate above 50%, well above the already high overall poverty rate of 20% in Lithuania.
Unemployment benefits (EUR per month) in the 2nd month of unemployment by previous gross income, 2021
Note: A long and continuous employment record is assumed to calculate unemployment benefits.
Source: (OECD, 2022[49]), based on OECD Tax and Benefit model (TaxBen)
Regarding tax incentives, the labour tax wedge in Lithuania has been reduced in 2019 but remains higher than the OECD average, especially around and below the average wage (Figure 1.25). Further reducing the labour tax wedge for individuals earning less than the average wage would contribute to increase the employment rate of low- and medium-skilled workers. This could be achieved by lowering employee social security contributions (SSC) and/or the personal income tax (PIT) up to the average wage and increasing PIT for higher incomes at the same time to ensure unchanged fiscal revenues and the continued financing of social expenditures. At 32% in 2023, the top PIT rate was among the lowest in the OECD.
For workers earning the gross minimum wage or a slightly higher wage that is set in reference to the minimum wage, this reform would increase net after-tax income and limit some work disincentives, especially when low-income workers resume work after an unemployment spell (OECD, 2022, pp. 144-160[49]). As two thirds of unemployed Lithuanians are estimated to receive additional income from informal work, both because poverty is high and formal work is not rewarding enough (Gasparėnienė, Remeikienė and Williams, 2022[47]), this reform would contribute to addressing poverty issues and would likely strengthen formal labour supply.
For workers earning between the minimum and the average wage, lower SSC and PIT would increase net income with no immediate impact on labour costs. In the longer term, it may contribute to limit future gross wage increases and thus boost formal labour demand for low- and medium-skilled workers.
Note: The above Figure reports the labour tax wedge for a single person with no child at different points of the gross wage distributions, in Lithuania (Panel A) and the average OECD country (Panel B). The labour tax wage is the ratio of income tax, plus employee and employer social security contributions, minus cash transfers, over total labour costs, expressed in percentage points.
Source: Taxing Wages 2024 (OECD, 2024[50])
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