In 2024, the average annual inflation rate in China ranged at around 0.2 percent compared to the previous year. For 2025, projections by the IMF expect slightly negative inflation. The monthly inflation rate in China dropped to negative values in the first quarter of 2025. Calculation of inflation The inflation rate is calculated based on the Consumer Price Index (CPI) for China. The CPI is computed using a product basket that contains a predefined range of products and services on which the average consumer spends money throughout the year. Included are expenses for groceries, clothes, rent, power, telecommunications, recreational activities, and raw materials (e.g. gas, oil), as well as federal fees and taxes. The product basked is adjusted every five years to reflect changes in consumer preference and has been updated in 2020 for the last time. The inflation rate is then calculated using changes in the CPI. As the inflation of a country is seen as a key economic indicator, it is frequently used for international comparison. China's inflation in comparison Among the main industrialized and emerging economies worldwide, China displayed comparatively low inflation in 2023 and 2024. In previous years, China's inflation ranged marginally above the inflation rates of established industrialized powerhouses such as the United States or the European Union. However, this changed in 2021, as inflation rates in developed countries rose quickly, while prices in China only increased moderately. According to IMF estimates for 2024, Zimbabwe was expected to be the country with the highest inflation rate, with a consumer price increase of about 561 percent compared to 2023. In 2023, Turkmenistan had the lowest price increase worldwide with prices actually decreasing by about 1.7 percent.

Inflation is an important measure of any country’s economy, and the Retail Price Index (RPI) is one of the most widely used indicators in the United Kingdom, with the rate expected to be 4.1 percent in 2025, compared with 3.6 percent in 2024. This followed 2022, when RPI inflation reached a rate of 11.6 percent, by far the highest annual rate during this provided time period. CPI vs RPI Although the Retail Price Index is a commonly utilized inflation indicator, the UK also uses a newer method of calculating inflation, the Consumer Price Index. The CPI, along with the CPIH (Consumer Price Index including owner occupiers' housing costs) are usually preferred by the UK government, but the RPI is still used in certain instances. Increases in rail fares for example, are calculated using the RPI, while increases in pension payments are calculated using CPI, when this is used as the uprating factor. The use of one inflation measure over the other can therefore have a significant impact on people’s lives in the UK. High inflation falls to more typical levels by 2024 Like the Retail Price Index, the Consumer Price Index inflation rate also reached a recent peak in October 2022. In that month, prices were rising by 11.1 percent and did not fall below double figures until April 2023. This fall was largely due to slower price increases in key sectors such as energy, which drove a significant amount of the 2022 wave of inflation. Inflation nevertheless remains elevated, fueled not only by high food inflation, but also by underlying core inflation. As of February 2025, the overall CPI inflation rate was 2.8 percent, although an uptick in inflation is expected later in the year, with a rate of 3.7 percent forecast for the third quarter of the year.

When deciding on how to estimate future prices, due to influences that are likely to affect a product, we should consider two factors: the expected inflation and the real price change. The rate of real price change allows us to plot a trend line based on time series reflecting existing or past market price, that is, on "facts". Usually, many potential users are not going to use sophisticated forecasting techniques to estimate future prices, preferring to rely on simple approximation techniques. If acceptable time price series is available, then the simplest approach is to evidence a trend line over time that can be extended into the future. This can be done with regression analysis. In working with historical data, we could arrive at a medium-term trend estimate, which excludes the effects of inflation. Although the real price of forest products does not usually vary in an exponential way, the normal practice in investment analyses is often simplified by compounding price using a real price change rate. We can get the annual rate of real price change (r) from a linearized model that allows us to keep the statistical robustness of a linear regression model (with statistics, confidence indicators and tests), but applying the compound rate approach used in mathematics of finance. To do that, the well-known basic formula for compounding Pn=P0 (1+r)^n, where: Pn = estimated price in year n P0= price in year 0 r = annual rate of real price change (the real compound rate) n = number of years from year 0

is transformed into that of a straight line by making a change of variables (linearization).

The proposed method is easy to reproduce and seems more orthodox than apply projections made using a simple straight-line model. Even though the straight-line represents an average variation over the years, from a mathematics of finance approach we should discuss price variation in terms of the annual compound rate. In Figure 1, you can see the differences between these approaches. If we have a clear trend in past real prices and the likelihood of a real price variation, we could make future price assumptions. If you agree with this statement and believe that price trend based on historical patterns is a significative information, then you should use r value gotten from the linearized model here proposed to project the price according to the previous compounding equation, where P0 is any real price calculated through the linearized compounding model (Table I). In Catalonia, most of forest products prices have not kept up with inflation and reflect a declining trend. A few others have just barely kept up with inflation. This is means that, despite moderate growth in nominal terms, the real price of almost all Catalan forest products presents a negative trend. For example, Scots pine sawlogs -the most representative harvested species in Catalonia (the 27% of the total volume yearly logged)- have dropped by an average of almost 2% per year since 1980.

It is argued that univariate long memory estimates based on ex post data tend to underestimate the persistence of ex ante variables (and, hence, that of the ex post variables themselves) because of the presence of unanticipated shocks whose short-run volatility masks the degree of long-range dependence in the data. Empirical estimates of long-range dependence in the Fisher equation are shown to manifest this problem and lead to an apparent imbalance in the memory characteristics of the variables in the Fisher equation. Evidence in support of this typical underestimation is provided by results obtained with inflation forecast survey data and by direct calculation of the finite sample biases. To address the problem of bias, the paper introduces a bivariate exact Whittle (BEW) estimator that explicitly allows for the presence of short memory noise in the data. The new procedure enhances the empirical capacity to separate low-frequency behaviour from high-frequency fluctuations, and it produces estimates of long-range dependence that are much less biased when there is noise contaminated data. Empirical estimates from the BEW method suggest that the three Fisher variables are integrated of the same order, with memory parameter in the range (0.75, 1). Since the integration orders are balanced, the ex ante real rate has the same degree of persistence as expected inflation, thereby furnishing evidence against the existence of a (fractional) cointegrating relation among the Fisher variables and, correspondingly, showing little support for a long-run form of Fisher hypothesis.

All data are expressed as a percentage, except for GDP per capita, net wages, total population, life expectancy, expected years of education, average years of schooling, life and non-life premium, total premium, bank deposits, financial assets and deposits of insurance companies, which are expressed in absolute terms.

Source of data:

1. Data on Life and Non-life premium, Total (gross) premium, Premium reserve data, Financial assets and Deposits of insurance companies are collected from the official reports of insurance supervision agencies: Insurance Supervision Agency in Montenegro (http://www.ano.me/en/), Croatian Financial Services Supervisory Agency (https://www.hanfa.hr/en/), National Bank of Serbia (https://www.nbs.rs/internet/english/, Insurance Supervision Agency of North Macedonia (http://aso.mk/en/?lang=en) and Financial Supervisory Authority in Albania (https://amf.gov.al/).
2. The economic indicators for the observed Western Balkan countries (GDP per capita, unemployment rate, inflation rate, net earnings and average effective deposit interest rate) are taken from the website Eurostat (https://ec.europa.eu/eurostat) and Statista (https://www.statista.com/)
3. All demographic indicators, except for the expected and average years of schooling and education index, were collected from the Eurostat and UNDP database (https://ec.europa.eu/eurostat/data/database; http://hdr.undp.org/en/countries/profiles/ ).
4. Data on expected and average school years were taken from the UNESCO Institute for Statistics (http://uis.unesco.org) , while the education index was obtained as a result of a calculation based on a formula published on the UNDP website (http://hdr.undp.org/en/content/education-index).
5. Data on bond yield were collected from the website of European Commission (https://ec.europa.eu/), i.e. from EC reports - EU Candidate Countries’ & Potential Candidates’ Economic Quarterly (CCEQ), except two data for Serbia (2006 and 2007) which were estimated by Makima extrapolation.
6. Bank deposits data are taken from the official reports of banks' regulatory institutions: Central bank of Montenegro (https://www.cbcg.me/en), National bank of Serbia (https://www.nbs.rs/en/indeks/), Croatian National bank (https://www.hnb.hr/en/home), National bank of the Republic of North Macedonia (https://www.nbrm.mk/pocetna-en.nspx); Bank of Albania (https://www.bankofalbania.org/home/)

Description of columns:

f1-GDPper capita; f2- Unemployment (%); f3-Inflation rate (%); f4- Net Wages €; f5- Deposit rate (%); f6- Population; f7- Female (%); f8- Population <15 (%); f9- Population 15-64 (%); f10- Dep old (%); f11- Dep young (%); f12- Urban population (%); f13-Life exp. (years); f14- Preschool enroll rate (%); f15- Elem school enroll rate (%); f16-High school enroll rate (%); f17- University enroll rate (%); f18- Expected years of schooling; f19- Avg. years of schooling; f20- Education Index (%); f21- Fertility rate (number of children to a woman); f22- Birth rate (per 1000 inhabitants); f23- Health costs (% GDP); f24-premium reserve per GDP,

i1- life premium €; i2- non-life premium €; i3- total premium €; i4- bond yield (%); i5a- bank deposits ( national currency); i5b- bank deposits €; i6a-financial assets in insurance (national currency); i6b- financial assets in insurance €; i7a- deposits of insurers (national currency); i7b –deposit of insurers €

The inflation rate for the Retail Price Index (RPI) in the United Kingdom was 4.3 percent in May 2025, down from 4.5 percent in the previous month. From 2021 onwards, prices in the UK rose rapidly, with the RPI inflation rate peaking at 14.2 percent in October 2022. Although inflation fell in subsequent months, it wasn't until July 2023 that inflation fell below double digits, and as of late 2024, the RPI rate was still above three percent. The CPI and CPIH While the retail price index is still a popular method of calculating inflation, the consumer price index (CPI) is the current main measurement of inflation in the UK. There is also an additional price index, which includes some extra housing costs, known as the Consumer Price Index including homer occupiers' costs (CPIH) index, which is seen by the UK's Office of National Statistics as the official inflation rate. As of December 2024, the CPI inflation rate stood at 2.5 percent, while the CPIH rate was 3.5 percent. Core inflation down in 2024 Another way of measuring inflation is to strip out the volatility of energy and food prices and look at the underlying core inflation rate. As of December 2024, this was 3.2 percent, slightly higher than the overall CPI rate, but more aligned with the overall figure than it was in 2022 and 2023. When inflation peaked at 11.2 percent in October 2022, for example, core inflation stood at just 6.5 percent. After energy prices in 2023 fell relative to 2022, the overall inflation rate in the UK declined quite rapidly, with core inflation overtaking the overall rate in July 2023. During the most recent period of high inflation, core inflation peaked at 7.1 percent in May 2023, and while taking longer to fall than the overall figure, has generally been declining since then.