Inflation Rate in Lithuania increased to 3.70 percent in June from 3.40 percent in May of 2025. This dataset provides - Lithuania Inflation Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Ten-Year Expected Inflation and Real and Inflation Risk Premia is a part of the Inflation Expectations indicator of the Federal Reserve Bank of Cleveland.

Lithuania LT: Inflation:(GDP) Gross Domestic ProductDeflator data was reported at 4.254 % in 2017. This records an increase from the previous number of 0.951 % for 2016. Lithuania LT: Inflation:(GDP) Gross Domestic ProductDeflator data is updated yearly, averaging 2.533 % from Dec 1996 (Median) to 2017, with 22 observations. The data reached an all-time high of 18.982 % in 1996 and a record low of -3.295 % in 2009. Lithuania LT: Inflation:(GDP) Gross Domestic ProductDeflator data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Lithuania – Table LT.World Bank.WDI: Inflation. Inflation as measured by the annual growth rate of the GDP implicit deflator shows the rate of price change in the economy as a whole. The GDP implicit deflator is the ratio of GDP in current local currency to GDP in constant local currency.; ; World Bank national accounts data, and OECD National Accounts data files.; Median;

We report average expected inflation rates over the next one through 30 years. Our estimates of expected inflation rates are calculated using a Federal Reserve Bank of Cleveland model that combines financial data and survey-based measures. Released monthly.

In 2024, the average inflation rate in Lithuania stood at about 0.85 percent. Between 1996 and 2024, the figure dropped by approximately 22.24 percentage points, though the decline followed an uneven course rather than a steady trajectory. From 2024 to 2030, the inflation will rise by around 1.65 percentage points, showing an overall upward trend with periodic ups and downs.This indicator measures inflation based upon the year-on-year change in the average consumer price index, expressed in percent. The latter expresses a country's average level of prices based on a typical basket of consumer goods and services.

Expected Inflation Term Structure is a part of the Inflation Expectations indicator of the Federal Reserve Bank of Cleveland.

Inflation Rate in Turkey decreased to 35.05 percent in June from 35.41 percent in May of 2025. This dataset provides the latest reported value for - Turkey Inflation Rate - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

Lithuania LT: Harmonised Core Inflation Index data was reported at 1.490 Index, 2015 in Dec 2025. This records an increase from the previous number of 1.483 Index, 2015 for Sep 2025. Lithuania LT: Harmonised Core Inflation Index data is updated quarterly, averaging 0.952 Index, 2015 from Mar 1996 (Median) to Dec 2025, with 120 observations. The data reached an all-time high of 1.490 Index, 2015 in Dec 2025 and a record low of 0.625 Index, 2015 in Mar 1996. Lithuania LT: Harmonised Core Inflation Index data remains active status in CEIC and is reported by Organisation for Economic Co-operation and Development. The data is categorized under Global Database’s Lithuania – Table LT.OECD.EO: Consumer and Wholesale Price Index: Forecast: OECD Member: Quarterly. PCOREH - Core inflation index, harmonised Overall index excluding energy, food, alcohol and tobaccoIndex, national reference year; All items less energy, food, alcohol and tobacco

Ten-Year TIPS Yields versus Real Yields is a part of the Inflation Expectations indicator of the Federal Reserve Bank of Cleveland.

The statistic shows the average inflation rate in Turkey from 1987 to 2024, with projections up until 2030. In 2024, the average inflation rate in Turkey was at around 58.51 percent compared to the previous year. Turkey’s economy With a continuously growing gross domestic product /GDP and thus a rising share in the global GDP adjusted for Purchasing Power Parity, Turkey’s economy is one of the largest worldwide. By 2030, Turkey is estimated to be one of the countries with the highest gross domestic product worldwide. Import of goods figures and export figures are rising as well, however, the trade balance of Turkey has been in the negative range for several years now with a downwards trend which indicates a serious trade deficit – or in other words: an imbalance between export and import costs; the value of goods Turkey imports is a lot higher than the value of exported goods. Main export partners of Turkey for textiles, automotive goods, iron and steel, among other goods, are mostly European countries, with Germany leading the ranking, followed by Iraq, Great Britain, Italy and France. The most important economic sector for Turkey is the services sector, especially the tourism sector, which has experienced a significant boost over the last decade. Thus, Turkey is now among the most popular destinations for visitors of all nations. A look at gross domestic product /GDP growth in Turkey shows that the country suffered a brief setback during the economic crisis of 2008, but swiftly recovered and was back in the black by 2010. Turkey’s employment figures hardly suffered at all, they too recovered quickly and are now back to pre-crisis levels.

Lithuania LT: NAIRU: Equilibrium Unemployment Rate data was reported at 6.680 % in 2022. This records a decrease from the previous number of 6.683 % for 2021. Lithuania LT: NAIRU: Equilibrium Unemployment Rate data is updated yearly, averaging 7.322 % from Dec 2002 (Median) to 2022, with 21 observations. The data reached an all-time high of 9.571 % in 2011 and a record low of 5.965 % in 2002. Lithuania LT: NAIRU: Equilibrium Unemployment Rate data remains active status in CEIC and is reported by Organisation for Economic Co-operation and Development. The data is categorized under Global Database’s Lithuania – Table LT.OECD.EO: Non-Accelerating Inflation Rate of Unemployment (NAIRU): Forecast: OECD Member: Annual. NAIRU - Equilibrium unemployment rate The equilibrium unemployment rate (code NAIRU) is estimated using a Kalman filter in a Phillips curve framework which assumes inflation expectations are anchored at the central bank’s inflation target . The NAIRU is then projected forward from the last estimated period using a simple autoregressive rule, exceptionally modified to account for recent labour market reforms, until the end of the forecasting horizon More details on methodology in Rusticelli E., Turner D. and M. C. Cavalleri (2015), Incorporating anchored inflation expectations in the Phillips Curve and in the derivation of OECD measures of equilibrium unemployment, OECD Economics Department Working Papers No.1231 OECD, Economics Department Working Papers: Incorporating anchored inflation expectations in the Phillips Curve and in the derivation of OECD measures of equilibrium unemployment:https://www.oecd-ilibrary.org/economics/incorporating-anchored-inflation-expectations-in-the-phillips-curve-and-in-the-derivation-of-oecd-measures-of-equilibrium-unemployment_5js1gmq551wd-en

Lithuania LT: Harmonised Core Inflation Index: Double Hit Scenario data was reported at 1.117 Index, 2015 in Dec 2021. This records an increase from the previous number of 1.113 Index, 2015 for Sep 2021. Lithuania LT: Harmonised Core Inflation Index: Double Hit Scenario data is updated quarterly, averaging 0.937 Index, 2015 from Mar 1996 (Median) to Dec 2021, with 104 observations. The data reached an all-time high of 1.117 Index, 2015 in Dec 2021 and a record low of 0.625 Index, 2015 in Mar 1996. Lithuania LT: Harmonised Core Inflation Index: Double Hit Scenario data remains active status in CEIC and is reported by Organisation for Economic Co-operation and Development. The data is categorized under Global Database’s Lithuania – Table LT.OECD.EO: Consumer and Wholesale Price Index: Forecast: OECD Member: Quarterly. PCOREH - Core inflation index, harmonised Overall index excluding energy, food, alcohol and tobaccoIndex, national reference year Eurostat Harmonised indices of consumer prices:https://ec.europa.eu/eurostat/cache/metadata/en/prc_hicp_esms.htm; All items less energy, food, alcohol and tobacco

Lithuania LT: Harmonised Core Inflation Index: YoY: Double Hit Scenario data was reported at 1.432 % in Dec 2021. This records an increase from the previous number of 1.086 % for Sep 2021. Lithuania LT: Harmonised Core Inflation Index: YoY: Double Hit Scenario data is updated quarterly, averaging 1.588 % from Mar 1997 (Median) to Dec 2021, with 100 observations. The data reached an all-time high of 13.528 % in Mar 1997 and a record low of -2.605 % in Mar 2010. Lithuania LT: Harmonised Core Inflation Index: YoY: Double Hit Scenario data remains active status in CEIC and is reported by Organisation for Economic Co-operation and Development. The data is categorized under Global Database’s Lithuania – Table LT.OECD.EO: Consumer and Wholesale Price Index: Forecast: OECD Member: Quarterly. PCOREH_YTYPCT - Harmonised core inflationOverall index excluding energy, food, alcohol and tobacco Eurostat Harmonised indices of consumer prices:https://ec.europa.eu/eurostat/cache/metadata/en/prc_hicp_esms.htm; All items less food, energy, tobacco, alcohol

Lithuania LT: Harmonised Core Inflation Index: YoY: Single Hit Scenario data was reported at 2.090 % in Dec 2021. This records an increase from the previous number of 2.015 % for Sep 2021. Lithuania LT: Harmonised Core Inflation Index: YoY: Single Hit Scenario data is updated quarterly, averaging 1.657 % from Mar 1997 (Median) to Dec 2021, with 100 observations. The data reached an all-time high of 13.528 % in Mar 1997 and a record low of -2.605 % in Mar 2010. Lithuania LT: Harmonised Core Inflation Index: YoY: Single Hit Scenario data remains active status in CEIC and is reported by Organisation for Economic Co-operation and Development. The data is categorized under Global Database’s Lithuania – Table LT.OECD.EO: Consumer and Wholesale Price Index: Forecast: OECD Member: Quarterly. PCOREH_YTYPCT - Harmonised core inflationOverall index excluding energy, food, alcohol and tobacco Eurostat Harmonised indices of consumer prices:https://ec.europa.eu/eurostat/cache/metadata/en/prc_hicp_esms.htm; All items less food, energy, tobacco, alcohol

Market Overview:

The global light truck tire LT market is expected to grow at a CAGR of 5.5% from 2022 to 2030. The growth in the market can be attributed to the increasing demand for light trucks and SUVs, rising disposable income, and technological advancements in the automotive industry. In addition, the increasing popularity of light trucks and SUVs is expected to drive market growth.

Product Definition:

Light Truck Tire LT is a type of tire for light trucks and SUVs. It is designed to provide better handling and performance than a standard truck or SUV tire. It has an advantage over other types of tires because it is lightweight and has a low profile. This makes it easier to steer and drive, which makes it a better choice for truckers and SUV drivers.

Bias Tire:

A bias tire is a type of tire that has two different types of rubber on the inside and outside of the tire. This allows the bias to rotate more easily, which in turn gives the tire better handling characteristics. The outer layer is biased, which means it's oriented in one direction more than the other. This makes the tire more responsive and stable when cornering and braking.

Radial Tire:

The radial tire is a type of tire that is designed to be used in heavy vehicles such as trucks and buses. The design of the radial tire makes it possible to fit more than two tires onto the rim of a wheel, thereby increasing its diameter. Radial tires are also known as half-radial tires or simply radials because they have six equally spaced lugs around the outer edge.

Application Insights:

Truck tire accounted for the largest share in 2015 and is projected to continue their dominance over the forecast period. The segment will witness significant growth on account of rising demand from construction, mining, agricultural and utility applications.

The bus tire segment is expected to grow at a faster rate than that of truck tires during the forecast period owing to increased government funding for public transport systems which in turn will lead to an increase in passenger traffic on buses resulting in higher demand for Bus Tires.

Regional Analysis:

North America is expected to be the largest regional market. The growth can be attributed to the increasing demand for light trucks in countries such as the United States and Canada. Furthermore, there is a growing trend of using light trucks for commercial purposes, which will drive up the demand for truck tires in this region. Latin America is expected to grow at a slower pace than other regions due to high inflation rates and a weak economy in some countries. This growth can be attributed to increased sales of LT tires among small and medium-sized businesses (SMBs) in Latin America. Europe is expected to witness moderate growth over the forecast period owing to sluggish economic conditions in some countries such as Italy and Spain. In addition, stringent emission regulations are hampering the sales of heavy-duty LT tires in Europe. Asia Pacific is expected to be the fastest-growing regional market. The growth can be attributed to the increasing demand for light trucks in countries such as India, China, and Japan. In addition, rising disposable income levels among consumers will boost the sales of passenger cars and subsequently influence LT tire manufacturers in this region.

Growth Factors:

• Growing popularity of SUVs and crossovers: The growing popularity of SUVs and crossovers is another key factor driving the growth of the global light truck tire market. These vehicles are equipped with larger wheels and tires, which require special tires that offer superior performance characteristics compared to those used in traditional passenger cars.
• Technological advancements in tire manufacturing: Tire manufacturers are constantly investing in new technologies to improve the quality, durability, and performance of their products. This is helping them gain a stronger foothold in the global light truck tire market.
• Rising concerns over vehicle safety: With governments across the globe implementing stringent safety regulations, vehicle manufacturers are increasingly focusing on equipping their vehicles with advanced safety features such as airbags and anti-lock braking systems (ABS). This is also contributing to the growth of the global light truck tire market.

Report Scope

Lithuania LT: Harmonised Consumer Price Index (CPI): YoY data was reported at 2.422 % in Dec 2026. This stayed constant from the previous number of 2.422 % for Sep 2026. Lithuania LT: Harmonised Consumer Price Index (CPI): YoY data is updated quarterly, averaging 2.405 % from Mar 1997 (Median) to Dec 2026, with 120 observations. The data reached an all-time high of 21.472 % in Sep 2022 and a record low of -1.499 % in Mar 2003. Lithuania LT: Harmonised Consumer Price Index (CPI): YoY data remains active status in CEIC and is reported by Organisation for Economic Co-operation and Development. The data is categorized under Global Database’s Lithuania – Table LT.OECD.EO: Consumer and Wholesale Price Index: Forecast: OECD Member: Quarterly. CPIH_YTYPCT-Harmonised headline inflation The CPIH year-on-year changes is a measure of inflation

Lithuania LT: NAIRU: Unemployment Gap data was reported at -0.915 % in 2022. This records an increase from the previous number of -1.466 % for 2021. Lithuania LT: NAIRU: Unemployment Gap data is updated yearly, averaging -1.466 % from Dec 2002 (Median) to 2022, with 21 observations. The data reached an all-time high of 3.727 % in 2007 and a record low of -8.469 % in 2010. Lithuania LT: NAIRU: Unemployment Gap data remains active status in CEIC and is reported by Organisation for Economic Co-operation and Development. The data is categorized under Global Database’s Lithuania – Table LT.OECD.EO: Non-Accelerating Inflation Rate of Unemployment (NAIRU): Forecast: OECD Member: Annual. GAPUNR - Unemployment gap Difference of nairu and unemployment rate OECD calculation, see OECD Economic Outlook, Database Inventory OECD Economic Outlook, Database Inventory:https://www.oecd.org/eco/outlook/Database_Inventory.pdf

Timor-Leste TL: Inflation:(GDP) Gross Domestic ProductDeflator: Linked Series data was reported at 27.391 % in 2017. This records an increase from the previous number of -19.457 % for 2016. Timor-Leste TL: Inflation:(GDP) Gross Domestic ProductDeflator: Linked Series data is updated yearly, averaging 7.660 % from Dec 2001 (Median) to 2017, with 17 observations. The data reached an all-time high of 38.560 % in 2008 and a record low of -36.516 % in 2015. Timor-Leste TL: Inflation:(GDP) Gross Domestic ProductDeflator: Linked Series data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Timor-Leste – Table TL.World Bank.WDI: Inflation. Inflation as measured by the annual growth rate of the GDP implicit deflator shows the rate of price change in the economy as a whole. This series has been linked to produce a consistent time series to counteract breaks in series over time due to changes in base years, source data and methodologies. Thus, it may not be comparable with other national accounts series in the database for historical years.; ; World Bank staff estimates based on World Bank national accounts data archives, OECD National Accounts, and the IMF WEO database.; ;

These are the MCMC and nested sampling inference products and input files that were used to compute results for the paper "Finite inflation in cuved space" by L. T. Hergt, F. J. Agocs, W. J. Handley, M. P. Hobson, and A. N. Lasenby from 2022.

Example plotting scripts (as \(\texttt{.ipynb}\) or as \(\texttt{.html}\) files) and figures from the paper are included to demonstrate usage.

We used the following python packages for the genertion of MCMC and nested sampling chains:

Filename conventions:

• \(\texttt{mcmc}\): MCMC run
• \(\texttt{pcs#d####}\): PolyChord run (in synchronous mode) with \(\texttt{#d}\) repeats per parameter block (where \(\texttt{d}\) is the number of parameters in that block) and with \(\texttt{####}\) live points.
• \(\texttt{_cl_hf}\): Using Boltzmann theory code CLASS with nonlinearities code halofit.
• \(\texttt{_p18}\): Using Planck 2018 CMB data.
• \(\texttt{_TTTEEE}\): Using the high-l TTTEEE likelihood.
• \(\texttt{_TTTEEElite}\): Using the lite version of the high-l TTTEEE likelihood.
• \(\texttt{_lowl_lowE}\): Using the low-l likelihoods for temperature and E-modes.
• \(\texttt{_BK15}\): Using data from the 2015 observing season of Bicep2 and the Keck Array.
• \(\texttt{lcdm}\): Concordance cosmological model called LCDM (standard 6 cosmological sampling parameters, no tensor perturbations, zero spatial curvature)
• \(\texttt{_r}\): Extension with a variable tensor-to-scalar ratio \(r\).
• \(\texttt{_omegak}\): Extension with a variable curvature density parameter \(\Omega_K \).
• \(\texttt{_H0}\): Sampling over \(H_0\) instead of \(\theta_\mathrm{s}\).
• \(\texttt{_omegakh2}\): Extension with a variable curvature density parameter, but sampling over \(H_0\) instead of \(\theta_\mathrm{s}\) and over \(\omega_K\equiv\Omega_Kh^2\) instead of \(\Omega_K \).
• \(\texttt{_mn2}\): Using a quadratic monomial potential for the computation of the primordial universe.
• \(\texttt{_nat}\): Using the natural inflation potential for the computation of the primordial universe.
• \(\texttt{_stb}\): Using the Starobinsky potential for the computation of the primordial universe.
• \(\texttt{_AsfoH}\): Using the primordial sampling parameters {`logA_SR`, `N_star`, `f_i`, `omega_K`, `H0`}.
• \(\texttt{_perm}\): Assuming a permissive reheating scenario.

Europe's clothing manufacturing industry is largely driven by its reputation for upscale brands and high-end fashion. Countries like Italy and France have a renowned reputation for manufacturing high-quality apparel, which is in demand globally. As a result, industry revenue largely follows trends in disposable income and consumer spending. Clothing manufacturers have faced challenges brought on by the COVID-19 pandemic, severe inflation and foreign competition. Despite these challenges, the digital revolution has inspired new avenues for growth with the rise of e-commerce, which has become an increasingly central consumer shopping practice. Revenue is expected to hike at a compound annual rate of 0.5% to just over €100 billion over the five years through 2025, including a 3.2% drop in 2025. In 2020, like numerous sectors, the clothing industry took a heavy hit from the COVID-19 outbreak. Temporary restrictions curbed manufacturing activities and closed down physical retail markets, reducing consumer demand for clothes. The industry noticed some recovery as these restrictions eased, and consumers, who'd accumulated savings during lockdown periods, indulged in retail therapy – spending on clothing to bring personal joy. However, soaring inflation in 2022 dampened enthusiasm again. Raw material and energy costs soared, reducing manufacturers' profitability. Inflation has been subsiding since late 2023, though geopolitical tensions, including the ongoing Red Sea crisis and trade wars started by US President Donald Trump in early 2025, are renewing concerns of supply chain disruptions and heightened production costs. Looking forward, Europe’s clothing manufacturers will have to take the rough with the smooth. The growth of online shopping is not likely to slow down. Internationally, Europe maintains a strong reputation for quality, ensuring solid demand for its products. Revenue is forecast to grow at a compound annual rate of 0.6% to €102.8 billion over the five years through 2030. The challenge of sustainability is also stimulating innovation. The industry will continue to develop green solutions to production and use more eco-friendly materials. Technological advances in AI, 3D printing and automation are another cause for optimism, as these help to increase production efficiency. Personalisation of products is another trend that will drive customer satisfaction and build brand loyalty, supporting demand.