During the financial year 2026, 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.

The statistic shows the inflation rate in India from 1987 to 2024, with projections up until 2030. The inflation rate is calculated using the price increase of a defined product basket. This product basket contains products and services, on which the average consumer spends money throughout the year. They include expenses for groceries, clothes, rent, power, telecommunications, recreational activities and raw materials (e.g. gas, oil), as well as federal fees and taxes. In 2024, the inflation rate in India was around 4.67 percent compared to the previous year. See figures on India's economic growth for additional information. India's inflation rate and economy Inflation is generally defined as the increase of prices of goods and services over a certain period of time, as opposed to deflation, which describes a decrease of these prices. Inflation is a significant economic indicator for a country. The inflation rate is the rate at which the general rise in the level of prices, goods and services in an economy occurs and how it affects the cost of living of those living in a particular country. It influences the interest rates paid on savings and mortgage rates but also has a bearing on levels of state pensions and benefits received. A 4 percent increase in the rate of inflation in 2011 for example would mean an individual would need to spend 4 percent more on the goods he was purchasing than he would have done in 2010. India’s inflation rate has been on the rise over the last decade. However, it has been decreasing slightly since 2010. India’s economy, however, has been doing quite well, with its GDP increasing steadily for years, and its national debt decreasing. The budget balance in relation to GDP is not looking too good, with the state deficit amounting to more than 9 percent of GDP.

Inflation Rate in India increased to 2.07 percent in August from 1.61 percent in July of 2025. This dataset provides - India Inflation Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Cost of food in India decreased 0.69 percent in August of 2025 over the same month in the previous year. This dataset provides - India Food Inflation - actual values, historical data, forecast, chart, statistics, economic calendar and news.

As of July 2025, consumer price index (CPI) inflation in India eased to **** percent from *** percent in the corresponding month last year. This marked an eight-year low and lower than the Reserve Bank of India's tolerance band. CPI is the main measure of inflation in India.

The dataset contains Year and State wise State-wise Average Inflation (CPI) - General, Food and Beverages, Fuel and Light and Housing (Urban)

Note: General: 1. Data for Arunachal Pradesh is not available. 2. For calculating State-wise Consumer Price Index (CPI) inflation in 2020-21 the average CPI Index for ten months has been taken due to unavailability of CPI data for the months of April and May 2020. 3. Figures for Jammu & Kashmir from October 2019 pertain to combined Union Territories of Jammu & Kashmir and Ladakh (erstwhile State of Jammu & Kashmir)

Food and Beverages: 1. Data for Arunachal Pradesh is not available. 2. For 2019-20, annual inflation for all states is calculated using data from April-2019 to February-2020, and for All-India, it is calculated using April-2019 to March-2020 data. 3. For calculating State-wise CPI inflation in 2020-21 the average CPI for eight months has been taken due to unavailability of CPI data for the period April-July 2020. 4. Figures for Jammu & Kashmir from October 2019 pertain to combined Union Territories of Jammu & Kashmir and Ladakh(erstwhile State of Jammu & Kashmir)

Fuel and Light: 1. Data for Arunachal Pradesh is not available. 2. For 2019-20, annual inflation for all states is calculated using data from April-2019 to February-2020, and for All-India, it is calculated using April-2019 to March-2020 data. 3. For calculating State-wise CPI inflation in 2020-21 the average CPI for eight months has been taken due to unavailability of CPI data for the period April-July 2020. 4. Figures for Jammu & Kashmir from October 2019 pertain to combined Union Territories of Jammu & Kashmir and Ladakh (erstwhile State of Jammu & Kashmir)

Housing (Urban): 1. Data for Arunachal Pradesh is not available. 2. For 2019-20, annual inflation for all states is calculated using data from April-2019 to February-2020, and for All-India, it is calculated using April-2019 to March-2020 data. 3. For calculating State-wise CPI inflation in 2020-21 the average CPI for eight months has been taken due to unavailability of CPI data for the period April-July 2020. 4. Figures for Jammu & Kashmir from October 2019 pertain to combined Union Territories of Jammu & Kashmir and Ladakh (erstwhile State of Jammu & Kashmir)

Key information about India Core CPI Change

• India Core CPI Change was reported at 3.954 % in Feb 2025.
• This records an increase from the previous number of 3.673 % for Jan 2025.
• India Core CPI Change data is updated monthly, averaging 5.217 % from Jan 2012 to Feb 2025, with 158 observations.
• The data reached an all-time high of 10.350 % in Jan 2012 and a record low of 3.117 % in May 2024.
• India Core CPI Change data remains active status in CEIC and is reported by CEIC Data.
• The data is categorized under World Trend Plus’s Global Economic Monitor – Table: Core CPI: Y-o-Y Growth: Monthly.

The Consumer Price Index (CPI) is a measure that examines the weighted average of prices of a basket of consumer goods and services, such as transportation, food, and medical care. It is calculated by taking price changes for each item in the predetermined basket and averaging them. Prices are collected periodically, and the CPI is often used to measure inflation, reflecting the cost of living. The CPI is typically set against a base year. The index is set to 100 in the base year, and changes in the CPI indicate price changes compared to that year. A typical household might purchase a wide range of products and services. Items in the basket are weighted according to their importance or share in total household spending. The Inflation Rate is the percentage increase in the general level of prices for goods and services over a period of time. It indicates how much prices have risen over a specific period, typically a year. Higher inflation decreases the purchasing power of money, meaning consumers can buy less with the same amount of money.It reflects the overall health of an economy. Moderate inflation is expected in a growing economy, but hyperinflation can indicate economic instability. The Inflation Rate is calculated using the following formula: Inflation Rate (%) = ((CPI in Current Year−CPI in Previous Year)/ (CPI in Previous Year))×100

India IN: Consumer Price Index (CPI): YoY data was reported at 4.035 % in 2026. This records a decrease from the previous number of 4.196 % for 2025. India IN: Consumer Price Index (CPI): YoY data is updated yearly, averaging 5.932 % from Dec 1990 (Median) to 2026, with 37 observations. The data reached an all-time high of 13.399 % in 1991 and a record low of 3.383 % in 1999. India IN: 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 India – Table IN.OECD.EO: Consumer and Wholesale Price Index: Forecast: Non OECD Member: Annual. CPI_YTYPCT- Headline inflation The CPI year-on-year changes is a measure of inflation

Consumer Price Index CPI in India increased to 197 points in August from 196.10 points in July of 2025. This dataset provides - India Consumer Price Index (CPI) - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Key information about India Consumer Price Index CPI growth

• India Consumer Price Index (CPI) growth was measured at 3.6 % YoY in Feb 2025, compared with a rate of 4.3 % in the previous month.
• India Consumer Price Index growth data is updated monthly, available from Jan 1958 to Feb 2025, with an averaged number of 6.6 % YoY.
• The data reached an all-time high of 34.6 % YoY in Sep 1974 and a record low of -11.3 % YoY in Jun 1976.

Inflation Rate in Pakistan increased to 5.60 percent in September from 3 percent in August of 2025. This dataset provides the latest reported value for - Pakistan Inflation Rate - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

Key information about India Producer Price Index Growth

• India Producer Price Index (PPI) grew 2.4 % YoY in Dec 2024, compared with a growth of 1.9 % YoY in the previous month.
• India Producer Price Index data is updated monthly, available from Apr 1995 to Dec 2024, with an average change of 4.8 % YoY.
• The data reached an all-time high of 16.6 % YoY in May 2022 and a record low of -6.1 % YoY in Aug 2015.

As of December 2023, the retail price index of tables in India was approximately 150.7 This meant, the RPI of tables had increased by 50 percent compared to the base year of 2016.

Retail prices index is a measure of inflation published monthly by the Office for National Statistics. It measures the change in the cost of a representative sample of retail goods and services.

Key information about House Prices Growth

• India house prices grew 2.6% YoY in Sep 2024, following an increase of 6.2% YoY in the previous quarter.
• YoY growth data is updated quarterly, available from Mar 2011 to Sep 2024, with an average growth rate of 5.1%.
• House price data reached an all-time high of 30.6% in Mar 2011 and a record low of -11.4% in Sep 2020.

As of September 2025, Mumbai had the highest cost of living among other cities in the country, with an index value of ****. Gurgaon, a satellite city of Delhi and part of the National Capital Region (NCR) followed it with an index value of ****.  What is cost of living? The cost of living varies depending on geographical regions and factors that affect the cost of living in an area include housing, food, utilities, clothing, childcare, and fuel among others. The cost of living is calculated based on different measures such as the consumer price index (CPI), living cost indexes, and wage price index. CPI refers to the change in the value of consumer goods and services. The wage price index, on the other hand, measures the change in labor services prices due to market pressures. Lastly, the living cost indexes calculate the impact of changing costs on different households. The relationship between wages and costs determines affordability and shifts in the cost of living. Mumbai tops the list Mumbai usually tops the list of most expensive cities in India. As the financial and entertainment hub of the country, Mumbai offers wide opportunities and attracts talent from all over the country. It is the second-largest city in India and has one of the most expensive real estates in the world.

Supporting documentation on code lists, subject definitions, data accuracy, and statistical testing can be found on the American Community Survey website in the Data and Documentation section...Sample size and data quality measures (including coverage rates, allocation rates, and response rates) can be found on the American Community Survey website in the Methodology section..Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, for 2010, the 2010 Census provides the official counts of the population and housing units for the nation, states, counties, cities and towns. For 2006 to 2009, the Population Estimates Program provides intercensal estimates of the population for the nation, states, and counties..Explanation of Symbols:.An ''**'' entry in the margin of error column indicates that either no sample observations or too few sample observations were available to compute a standard error and thus the margin of error. A statistical test is not appropriate..An ''-'' entry in the estimate column indicates that either no sample observations or too few sample observations were available to compute an estimate, or a ratio of medians cannot be calculated because one or both of the median estimates falls in the lowest interval or upper interval of an open-ended distribution..An ''-'' following a median estimate means the median falls in the lowest interval of an open-ended distribution..An ''+'' following a median estimate means the median falls in the upper interval of an open-ended distribution..An ''***'' entry in the margin of error column indicates that the median falls in the lowest interval or upper interval of an open-ended distribution. A statistical test is not appropriate..An ''*****'' entry in the margin of error column indicates that the estimate is controlled. A statistical test for sampling variability is not appropriate. .An ''N'' entry in the estimate and margin of error columns indicates that data for this geographic area cannot be displayed because the number of sample cases is too small..An ''(X)'' means that the estimate is not applicable or not available..Estimates of urban and rural population, housing units, and characteristics reflect boundaries of urban areas defined based on Census 2000 data. Boundaries for urban areas have not been updated since Census 2000. As a result, data for urban and rural areas from the ACS do not necessarily reflect the results of ongoing urbanization..While the 2006-2010 American Community Survey (ACS) data generally reflect the December 2009 Office of Management and Budget (OMB) definitions of metropolitan and micropolitan statistical areas; in certain instances the names, codes, and boundaries of the principal cities shown in ACS tables may differ from the OMB definitions due to differences in the effective dates of the geographic entities..The methodology for calculating median income and median earnings changed between 2008 and 2009. Medians over $75,000 were most likely affected. The underlying income and earning distribution now uses $2,500 increments up to $250,000 for households, non-family households, families, and individuals and employs a linear interpolation method for median calculations. Before 2009 the highest income category was $200,000 for households, families and non-family households ($100,000 for individuals) and portions of the income and earnings distribution contained intervals wider than $2,500. Those cases used a Pareto Interpolation Method..Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted roughly as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see Accuracy of the Data). The effect of nonsampling error is not represented in these tables..Source: U.S. Census Bureau, 2006-2010 American Community Survey

Supporting documentation on code lists, subject definitions, data accuracy, and statistical testing can be found on the American Community Survey website in the Data and Documentation section...Sample size and data quality measures (including coverage rates, allocation rates, and response rates) can be found on the American Community Survey website in the Methodology section..Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, it is the Census Bureau''s Population Estimates Program that produces and disseminates the official estimates of the population for the nation, states, counties, cities and towns and estimates of housing units for states and counties..Explanation of Symbols:An ''**'' entry in the margin of error column indicates that either no sample observations or too few sample observations were available to compute a standard error and thus the margin of error. A statistical test is not appropriate..An ''-'' entry in the estimate column indicates that either no sample observations or too few sample observations were available to compute an estimate, or a ratio of medians cannot be calculated because one or both of the median estimates falls in the lowest interval or upper interval of an open-ended distribution..An ''-'' following a median estimate means the median falls in the lowest interval of an open-ended distribution..An ''+'' following a median estimate means the median falls in the upper interval of an open-ended distribution..An ''***'' entry in the margin of error column indicates that the median falls in the lowest interval or upper interval of an open-ended distribution. A statistical test is not appropriate..An ''*****'' entry in the margin of error column indicates that the estimate is controlled. A statistical test for sampling variability is not appropriate. .An ''N'' entry in the estimate and margin of error columns indicates that data for this geographic area cannot be displayed because the number of sample cases is too small..An ''(X)'' means that the estimate is not applicable or not available..Estimates of urban and rural population, housing units, and characteristics reflect boundaries of urban areas defined based on Census 2010 data. As a result, data for urban and rural areas from the ACS do not necessarily reflect the results of ongoing urbanization..While the 2010-2014 American Community Survey (ACS) data generally reflect the February 2013 Office of Management and Budget (OMB) definitions of metropolitan and micropolitan statistical areas; in certain instances the names, codes, and boundaries of the principal cities shown in ACS tables may differ from the OMB definitions due to differences in the effective dates of the geographic entities..Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted roughly as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see Accuracy of the Data). The effect of nonsampling error is not represented in these tables..Source: U.S. Census Bureau, 2010-2014 American Community Survey 5-Year Estimates

Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, the decennial census is the official source of population totals for April 1st of each decennial year. In between censuses, the Census Bureau's Population Estimates Program produces and disseminates the official estimates of the population for the nation, states, counties, cities, and towns and estimates of housing units and the group quarters population for states and counties..Information about the American Community Survey (ACS) can be found on the ACS website. Supporting documentation including code lists, subject definitions, data accuracy, and statistical testing, and a full list of ACS tables and table shells (without estimates) can be found on the Technical Documentation section of the ACS website.Sample size and data quality measures (including coverage rates, allocation rates, and response rates) can be found on the American Community Survey website in the Methodology section..Source: U.S. Census Bureau, 2019-2023 American Community Survey 5-Year Estimates.ACS data generally reflect the geographic boundaries of legal and statistical areas as of January 1 of the estimate year. For more information, see Geography Boundaries by Year..Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted roughly as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see ACS Technical Documentation). The effect of nonsampling error is not represented in these tables..Users must consider potential differences in geographic boundaries, questionnaire content or coding, or other methodological issues when comparing ACS data from different years. Statistically significant differences shown in ACS Comparison Profiles, or in data users' own analysis, may be the result of these differences and thus might not necessarily reflect changes to the social, economic, housing, or demographic characteristics being compared. For more information, see Comparing ACS Data..The Hispanic origin and race codes were updated in 2020. For more information on the Hispanic origin and race code changes, please visit the American Community Survey Technical Documentation website..Estimates of urban and rural populations, housing units, and characteristics reflect boundaries of urban areas defined based on 2020 Census data. As a result, data for urban and rural areas from the ACS do not necessarily reflect the results of ongoing urbanization..Explanation of Symbols:- The estimate could not be computed because there were an insufficient number of sample observations. For a ratio of medians estimate, one or both of the median estimates falls in the lowest interval or highest interval of an open-ended distribution. For a 5-year median estimate, the margin of error associated with a median was larger than the median itself.N The estimate or margin of error cannot be displayed because there were an insufficient number of sample cases in the selected geographic area. (X) The estimate or margin of error is not applicable or not available.median- The median falls in the lowest interval of an open-ended distribution (for example "2,500-")median+ The median falls in the highest interval of an open-ended distribution (for example "250,000+").** The margin of error could not be computed because there were an insufficient number of sample observations.*** The margin of error could not be computed because the median falls in the lowest interval or highest interval of an open-ended distribution.***** A margin of error is not appropriate because the corresponding estimate is controlled to an independent population or housing estimate. Effectively, the corresponding estimate has no sampling error and the margin of error may be treated as zero.

Inflation Rate in Sri Lanka increased to 1.50 percent in September from 1.20 percent in August of 2025. This dataset provides - Sri Lanka Inflation Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.