Inflation is generally defined as the continued increase in the average prices of goods and services in a given region. Following the extremely high global inflation experienced in the 1980s and 1990s, global inflation has been relatively stable since the turn of the millennium, usually hovering between three and five percent per year. There was a sharp increase in 2008 due to the global financial crisis now known as the Great Recession, but inflation was fairly stable throughout the 2010s, before the current inflation crisis began in 2021. Recent years Despite the economic impact of the coronavirus pandemic, the global inflation rate fell to 3.26 percent in the pandemic's first year, before rising to 4.66 percent in 2021. This increase came as the impact of supply chain delays began to take more of an effect on consumer prices, before the Russia-Ukraine war exacerbated this further. A series of compounding issues such as rising energy and food prices, fiscal instability in the wake of the pandemic, and consumer insecurity have created a new global recession, and global inflation in 2024 is estimated to have reached 5.76 percent. This is the highest annual increase in inflation since 1996. Venezuela Venezuela is the country with the highest individual inflation rate in the world, forecast at around 200 percent in 2022. While this is figure is over 100 times larger than the global average in most years, it actually marks a decrease in Venezuela's inflation rate, which had peaked at over 65,000 percent in 2018. Between 2016 and 2021, Venezuela experienced hyperinflation due to the government's excessive spending and printing of money in an attempt to curve its already-high inflation rate, and the wave of migrants that left the country resulted in one of the largest refugee crises in recent years. In addition to its economic problems, political instability and foreign sanctions pose further long-term problems for Venezuela. While hyperinflation may be coming to an end, it remains to be seen how much of an impact this will have on the economy, how living standards will change, and how many refugees may return in the coming years.

The Consumer Price Index of the United Kingdom was 138.5 in the second quarter of 2025, indicating that consumer prices have increased by 38.5 percent when compared with the first quarter of 2015. As of June 2025, the inflation rate for the CPI was 3.6 percent, an uptick from March, when prices were rising by 2.6 percent. A long period of elevated inflation between 2021 and 2023 peaked in October 2022 and saw prices increase by over 20 percent in just three years. Uptick in inflation expected in 2025 In late 2024, the UK's main economic forecaster, the Office for Budget Responsibility, predicted that the annual inflation rate for 2025 would average out at around 2.6 percent. In March 2025, however, the OBR revised this figure upward, with annual inflation now expected to be 3.2 percent. This uptick in inflation is predicted to peak in the third quarter of the year at 3.7 percent before falling to two percent by the second quarter of 2026. Although this period of higher inflation is predicted to be far less severe than in 2022, it will no doubt put further pressure on households already struggling with their cost of living. Cost of living woes continue The share of UK households reporting that their cost of living was increasing has been steadily rising since Summer 2024. At that time, less than half of UK households reported rising costs, down from 91 percent two years earlier. As of March 2025, however, 59 percent of households said their costs were rising, the highest figure since 2023. Of these households, 93 percent reported that their food shop was increasing, with three quarters of them reporting higher energy costs. With higher inflation predicted in 2025, the pressure on UK households will likely continue, although a crisis on the scale of 2021-2023 will hopefully be avoided.

Annual indexes for major components and special aggregates of the Consumer Price Index (CPI), for Canada, provinces, Whitehorse, Yellowknife and Iqaluit. Data are presented for the last five years. The base year for the index is 2002=100.

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In economics, the inflation rate is a measure of the change in price of a basket of goods. The most common measure being the consumer price index. It is the percentage rate of change in price level over time, and also indicates the rate of decrease in the purchasing power of money. The annual rate of inflation for 2023, was 4.1 percent higher in the United States when compared to the previous year. More information on inflation and the consumer price index can be found on our dedicated topic page. Additionally, the monthly rate of inflation in the United States can be accessed here. Inflation and purchasing power Inflation is a key economic indicator, and gives economists and consumers alike a look at changes in prices in the wider economy. For example, if an average pair of socks costs 100 dollars one year and 105 dollars the following year, the inflation rate is five percent. This means the amount of goods an individual can purchase with a unit of currency has decreased. This concept is often referred to as purchasing power. The data presents the average rate of inflation in a year, whereas the monthly measure of inflation measures the change in prices compared with prices one year ago. For example, monthly inflation in the U.S. reached a peak in June 2022 at 9.1 percent. This means that prices were 9.1 percent higher than they were in June of 2021. The purchasing power is the extent to which a person has available funds to make purchases. The Big Mac Index has been published by The Economist since 1986 and exemplifies purchasing power on a global scale, allowing us to see note the differences between different countries currencies. Switzerland for example, has the most expensive Big Mac in the world, costing consumers 6.71 U.S. dollars as of July 2022, whereas a Big Mac cost 5.15 dollars in the United States, and 4.77 dollars in the Euro area. One of the most important tools in influencing the rate of inflation is interest rates. The Federal Reserve of the United States has the capacity to make changes to the federal interest rate . Changes to the rate of inflation are thought to be an imbalance between supply and demand. After COVID-19 related lockdowns came to an end there was a sudden increase in demand for goods and services with consumers having more funds than usual thanks to reduced spending during lockdown and government funded economic support. Additionally, supply-chain related bottlenecks also due to lockdowns around the world and the Russian invasion of Ukraine meant that there was a decrease in the supply of goods and services. By increasing the interest rate, the Federal Reserve aims to reduce spending, and thus bring demand back into balance with supply.

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Living Conditions Survey (LCS): Households that cannot afford various expenses by annual income brackets of the household in 2007. National.

Morocco Living Cost Index: Tetouan: Clothing & Footwear data was reported at 204.100 1989=100 in Oct 2009. This stayed constant from the previous number of 204.100 1989=100 for Sep 2009. Morocco Living Cost Index: Tetouan: Clothing & Footwear data is updated monthly, averaging 198.800 1989=100 from Jan 2003 (Median) to Oct 2009, with 82 observations. The data reached an all-time high of 204.100 1989=100 in Oct 2009 and a record low of 194.400 1989=100 in Aug 2007. Morocco Living Cost Index: Tetouan: Clothing & Footwear data remains active status in CEIC and is reported by High Commission for Planning. The data is categorized under Global Database’s Morocco – Table MA.I008: Living Cost Index: 1989=100: by Region.

Consumer Price Index CPI in Puerto Rico increased to 137.89 points in June from 137.80 points in May of 2025. This dataset provides - Puerto Rico Consumer Price Index Cpi- actual values, historical data, forecast, chart, statistics, economic calendar and news.

Morocco Living Cost Index: FH: Household Appliances data was reported at 102.300 1989=100 in Oct 2009. This records a decrease from the previous number of 102.400 1989=100 for Sep 2009. Morocco Living Cost Index: FH: Household Appliances data is updated monthly, averaging 103.200 1989=100 from Dec 2002 (Median) to Oct 2009, with 83 observations. The data reached an all-time high of 106.900 1989=100 in Dec 2002 and a record low of 101.600 1989=100 in Jun 2007. Morocco Living Cost Index: FH: Household Appliances data remains active status in CEIC and is reported by High Commission for Planning. The data is categorized under Global Database’s Morocco – Table MA.I006: Living Cost Index: 1989=100: by Industry.

Abstract

The evaluation examines impacts of the Transportation Project in three ways. First, we calculate economic rates of return associated with reduced user costs for each rehabilitated road - and for the project in aggregate - making use of the before and after measures of road use, detailed data on project implementation and costs, and models that project changes in usage, costs, and benefits over time.

We also examine changes in the availability and cost of common consumption goods that can be attributed to the transportation project. This component of the analysis relies on a survey of retail establishments that targets goods in the Cansta Basica or basic basket that is used in Nicaragua to track consumer prices. Data was collected both before and after construction in communities both on and away from rehabilitated roads. The survey design therefore facilitates measurement of changes in price and availability of goods relative to a relevant comparison group.

The evaluation also examines changes in household consumption using a similar pre- and post- rehabilitation data collection methodology. The consumption measures for this component of the evaluation are derived from responses to household surveys implemented for the Rural Business Development (RBD) portion of the Nicaragua compact. While the bulk of the respondents to this survey are outside the zone of influence of the road rehabilitation, we identify more than one-hundred households within the zone of influence of the rehabilitated roads. It is important to recognize that the data for this component of the report was collected for a different purpose and respondents are not a representative sample of households in the treatment and control areas. Thus these results are intended to be suggestive and provide some insight on the robustness of results from the survey of retail establishments. These surveys do not provide unbiased estimates of the transportation project on the affected population.

Geographic coverage

Departments of Leon and Chinandega

Analysis unit

Retail establishments

Universe

Departments of Leon and Chinandega

Kind of data

Sample survey data [ssd]

Research instrument

Establishment surveys in thirty communities were conducted to collect data on price and availability of a basket of consumer goods to shed light on whether the rehabilitated roads provide significant nonuser benefits. The establishment survey contains information on fifty-three items that comprise the Canasta Basica - or basic basket - from which the Central Bank constructs its cost of living index. The fifty-three items in the Canasta Basica are segregated into eight categories that include food items, household costs, and clothing.

Inflation Rate in Serbia increased to 4.60 percent in June from 3.80 percent in May of 2025. This dataset provides - Serbia Inflation Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

State minimum wage is changed annually based on changes in the CPI and a cost of living formula.

For more information, visit https://www.dol.gov/whd/state/stateMinWageHis.htm

During the financial year 2023, the cost inflation index (CII) in India stood at ***. This was an increase from the previous year's figure of ***. The CII is used to compute an asset's inflation-adjusted cost price. It is used to assess the inflation value of assets like land, houses, jewelry etc.

Morocco Living Cost Index: Oujda: Clothing & Footwear data was reported at 184.800 1989=100 in Oct 2009. This records a decrease from the previous number of 184.900 1989=100 for Sep 2009. Morocco Living Cost Index: Oujda: Clothing & Footwear data is updated monthly, averaging 184.950 1989=100 from Jan 2003 (Median) to Oct 2009, with 82 observations. The data reached an all-time high of 188.400 1989=100 in Dec 2007 and a record low of 174.900 1989=100 in Jan 2003. Morocco Living Cost Index: Oujda: Clothing & Footwear data remains active status in CEIC and is reported by High Commission for Planning. The data is categorized under Global Database’s Morocco – Table MA.I008: Living Cost Index: 1989=100: by Region.

Inflation Rate in Colombia decreased to 4.82 percent in June from 5.05 percent in May of 2025. This dataset provides - Colombia Inflation Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Abstract

The CSES is a household survey with questions to households and the household members. In the household questionnaire there are a number of modules with questions relating to the living conditions, e.g. housing conditions, education, health, expenditure/income and labour force. It is designed to provide information on social and economic conditions of households for policy studies on poverty, household production and final consumption for the National Accounts and weights for the CPI.

The main objective of the survey is to collect statistical information about living standards of the population and the extent of poverty. Essential areas as household production and cash income, household level and structure of consumption including poverty and nutrition, education and access to schooling, health and access to medical care, transport and communication, housing and amenities and family and social relations. For recording expenditure, consumption and income the Diary Method was applied.

Another main objective of the survey is also to collect accurate statistical information about living standards of the population and the extent of poverty as an essential instrument to assist the government in diagnosing the problems and designing effective policies for reducing poverty, and in evaluating the progress of poverty reduction which are the main priorities in the "Rectangular Strategy" of the Royal Government of Cambodia.

Geographic coverage

National Coverage

Analysis unit

Households

Kind of data

Sample survey data [ssd]

Sampling procedure

The sampling design in the CSES survey is a three-stage design. In stage one a sample of villages is selected, in stage two an Enumeration Area (EA) is selected from each village selected in stage one, and in stage three a sample of households is selected from each EA selected in stage two. The sampling designs used in the three stages were: Stage 1: A stratified systematic pps6 sample of villages was selected. Strata were defined by provinces and the urban/rural classification of villages. The size measure used in the systematic pps sampling was the number of households in the village according to the population census 1998. Stage 2. One EA was selected by Simple Random Sampling (SRS), in each village selected in stage 1. Stage 3. In each selected EA a sample of households was selected by systematic sampling.

The design described above was used for the CSES 2004 survey.7 In 2007, a subsample of the villages, or EAs, in the 2004 sample was selected by SRS. The villages and EAs surveyed in 2007 were thus included in the sample in both years. In each selected EA a sample of households was selected by systematic sampling. The selected households in 2007 are not necessarily the same as those included in the sample in 2004.

The selection of households in stage three was done in field by first listing the households in the selected EA, and then selecting a systematic sample of households. Selected households were observed during one calendar month. The allocation of the households over the months in 2007 was done so that each village in the 2007 sample was observed in the same calendar month as in 2004. The sample size in 2007 was 360 villages or 3,600 households, compared to the sample for the 2004 survey of 720 villages or 12,000 households.

Some provinces were excluded, due to cost and other reasons, in the sample for 2007. The estimates are however, adjusted for the under coverage error caused by excluding those provinces. Please refer to Technical Documents for details.

Mode of data collection

Face-to-face [f2f]

Research instrument

Four different questionnaires or forms were used in the CSES 2007: 1. Household listing form The listing of households was used for sampling households, see section 4.3.

1. Village questionnaire The village questionnaire was responded by the village leader or a representative of the village leader. The questions are about economy and infrastructure, crop production, health, education, retail prices, rental and sales prices of land etc.

2. Household questionnaire The household questionnaire was responded by the head of the household, spouse of the head of the household or of another adult household member. The household questionnaire includes questions about housing conditions, crop production and other agricultural activities, liabilities, durable goods, construction activities and income from other sources than economic activity. It also includes questions for each household member about education and literacy, migration, current economic activity and employment, health, smoking, HIV/AIDS awareness, and victimization. Some of these questions were responded by the head of household/spouse and some were responded by each household member. The questions in the first part of the household questionnaire are posed during the initial visit to the household. This part includes questions about e.g. the household member's age, sex, marital status, relation to head of household, and questions about household expenditure/consumption of food and non-food items. During a survey month different questions have been asked different weeks according to the following: • Week 1. Questions about education, migration, and housing • Week 2. Questions about economic activity, agricultural and non-agricultural business, household liabilities and other incomes. • Week 3. Questions about construction, durable goods, and child health • Week 4. Questions about current economic activities, health and victimization

3. Diary sheet The diary sheet on daily household expenditure, including value of own production, and income have been filled in during the entire month.

Cleaning operations

A team of data editors, data coders and data entry staff was formed. The data editors were checking the questionnaires before the data entry and also took care of errors to ensure that entered data were consistent with the collected data in the questionnaires or diaries.

Response rate

Not Computed

Sampling error estimates

In order to provide a basis for assessing the reliability or precision of CSES estimates, the estimation of the magnitude of sampling error in the survey data were computed. Since most of the estimates from the survey are in the form of weighted ratios, variances for ratio estimates are presented.

The Coefficients of Variation (CV) on national level estimates are generally below 4 percent. The exception is the CV for total value of assets where there are rather high CVs especially in the urban areas, which should be expected. The CVs are somewhat higher in the urban and rural domains but still generally below 7 percent. For the five zones, the average CVs are in the range 5 to 13 percent with a few exceptions where the CVs are above 20 percent. For provinces the CVs for food consumption are 9 percent on average.

The sample take within Primary Sampling Units (PSU) was set to 10 households per PSU in the CSES 1999. When data on variances became available, it was possible to make crude calculations of the optimal sample take within PSU. Calculations on some of the central estimates in the CSES 1999 show that the design effects in most cases are in the range 1 to 5.

Intra-cluster correlation coefficients have been calculated based on the design effects. These correlation coefficients are somewhat high. The reason is that the characteristics that are measured tend to be concentrated (clustered) within the PSUs. The optimal sample size within PSUs under different assumptions on cost ratios and intra-cluster correlation coefficients was then calculated. The cost ratio is the average cost for adding a village to the sample divided by the average cost of including an extra household in the sample. In the CSES, it was chosen to adopt a fairly low cost ratio due to the fact that the interview time per household is long. Under this assumption the optimal sample size is probably around 10 households per village for many of the CSES indicators.

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Inflation Rate in Bangladesh decreased to 8.48 percent in June from 9.05 percent in May of 2025. This dataset provides the latest reported value for - Bangladesh Inflation Rate - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

Inflation Rate in Uganda decreased to 3.80 percent in July from 3.90 percent in June of 2025. This dataset provides - Uganda Inflation Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.