Money Supply M0 in India increased to 49621.32 INR Billion in May from 49099.34 INR Billion in April of 2025. This dataset includes a chart with historical data for India Money Supply M0.

India Money Supply: Currency with Public data was reported at 18,751,330.000 INR mn in Oct 2018. This records an increase from the previous number of 18,429,360.000 INR mn for Sep 2018. India Money Supply: Currency with Public data is updated monthly, averaging 219,610.000 INR mn from Mar 1951 (Median) to Oct 2018, with 812 observations. The data reached an all-time high of 18,767,620.000 INR mn in Jun 2018 and a record low of 11,670.000 INR mn in Oct 1952. India Money Supply: Currency with Public data remains active status in CEIC and is reported by Reserve Bank of India. The data is categorized under Global Database’s India – Table IN.KAA001: Money Supply.

India Money Supply: Deposit Money: Demand Deposits with Banks data was reported at 13,509,180.000 INR mn in Oct 2018. This records a decrease from the previous number of 14,231,970.000 INR mn for Sep 2018. India Money Supply: Deposit Money: Demand Deposits with Banks data is updated monthly, averaging 148,445.000 INR mn from Mar 1951 (Median) to Oct 2018, with 812 observations. The data reached an all-time high of 14,837,120.000 INR mn in Mar 2018 and a record low of 5,080.000 INR mn in Dec 1953. India Money Supply: Deposit Money: Demand Deposits with Banks data remains active status in CEIC and is reported by Reserve Bank of India. The data is categorized under Global Database’s India – Table IN.KAA001: Money Supply.

Money supply, billion currency units in India, March, 2025 The most recent value is 272143.55 billion Indian Rupee as of March 2025, an increase compared to the previous value of 268520.8 billion Indian Rupee. Historically, the average for India from May 1998 to March 2025 is 90306.74 billion Indian Rupee. The minimum of 8476.97 billion Indian Rupee was recorded in May 1998, while the maximum of 272143.55 billion Indian Rupee was reached in March 2025. | TheGlobalEconomy.com

Key information about India Money Supply M1

• India Money Supply M1 was reported at 724.128 USD bn in Feb 2025
• This records an increase from the previous number of 723.320 USD bn for Jan 2025
• India Money Supply M1 data is updated monthly, averaging 43.037 USD bn from Jan 1957 to Feb 2025, with 818 observations
• The data reached an all-time high of 754.597 USD bn in Jun 2024 and a record low of 4.709 USD bn in Aug 1957. India Money Supply M1 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: Money Supply M1: USD: Monthly

CEIC converts monthly Money Supply M1 into USD. The Reserve Bank of India provides Money Supply M1 in local currency. The Federal Reserve Board period end market exchange rate is used for currency conversions.

India Money Supply: Currency in Circulation: Small Coins data was reported at 7,430.000 INR mn in Oct 2018. This stayed constant from the previous number of 7,430.000 INR mn for Sep 2018. India Money Supply: Currency in Circulation: Small Coins data is updated monthly, averaging 11,075.000 INR mn from Mar 1994 (Median) to Oct 2018, with 296 observations. The data reached an all-time high of 26,830.000 INR mn in Sep 2005 and a record low of 7,340.000 INR mn in Aug 2011. India Money Supply: Currency in Circulation: Small Coins data remains active status in CEIC and is reported by Reserve Bank of India. The data is categorized under Global Database’s India – Table IN.KAA001: Money Supply.

Graph and download economic data for Monetary Aggregates and Their Components: Broad Money and Components: M3 for India (MABMM301INM189N) from Jan 1960 to Sep 2023 about M3, broad, India, and monetary aggregates.

Money Supply M2 in India increased to 67732.92 INR Billion in March from 65376.10 INR Billion in February of 2025. This dataset provides - India Money Supply M2 - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Current and historical data on India's Money Supply (M3) - sources, components, currency in circulation, and comparison with global peers.

India Money Supply: M4 data was reported at 157,393,240.000 INR mn in Apr 2019. This records a decrease from the previous number of 157,888,260.000 INR mn for Mar 2019. India Money Supply: M4 data is updated monthly, averaging 30,505,320.000 INR mn from Mar 1994 (Median) to Apr 2019, with 302 observations. The data reached an all-time high of 157,888,260.000 INR mn in Mar 2019 and a record low of 4,382,910.000 INR mn in Mar 1994. India Money Supply: M4 data remains active status in CEIC and is reported by Reserve Bank of India. The data is categorized under Global Database’s India – Table IN.KAA001: Money Supply.

Abstract

Financial inclusion is critical in reducing poverty and achieving inclusive economic growth. When people can participate in the financial system, they are better able to start and expand businesses, invest in their children’s education, and absorb financial shocks. Yet prior to 2011, little was known about the extent of financial inclusion and the degree to which such groups as the poor, women, and rural residents were excluded from formal financial systems.

By collecting detailed indicators about how adults around the world manage their day-to-day finances, the Global Findex allows policy makers, researchers, businesses, and development practitioners to track how the use of financial services has changed over time. The database can also be used to identify gaps in access to the formal financial system and design policies to expand financial inclusion.

Geographic coverage

National Coverage. Sample excludes Northeast states and remote islands. In addition, some districts in Assam, Bihar, Jammu and Kashmir, Jharkhand, and Uttar Pradesh were replaced because of security concerns. The excluded areas represent less than 10% of the population.

Analysis unit

Individual

Universe

The target population is the civilian, non-institutionalized population 15 years and above.

Kind of data

Sample survey data [ssd]

Frequency of data collection

Triennial

Sampling procedure

As in the first edition, the indicators in the 2014 Global Findex are drawn from survey data covering almost 150,000 people in more than 140 economies-representing more than 97 percent of the world's population. The survey was carried out over the 2014 calendar year by Gallup, Inc. as part of its Gallup World Poll, which since 2005 has continually conducted surveys of approximately 1,000 people in each of more than 160 economies and in over 140 languages, using randomly selected, nationally representative samples. The target population is the entire civilian, noninstitutionalized population age 15 and above. The set of indicators will be collected again in 2017.

Surveys are conducted face to face in economies where telephone coverage represents less than 80 percent of the population or is the customary methodology. In most economies the fieldwork is completed in two to four weeks. In economies where face-to-face surveys are conducted, the first stage of sampling is the identification of primary sampling units. These units are stratified by population size, geography, or both, and clustering is achieved through one or more stages of sampling. Where population information is available, sample selection is based on probabilities proportional to population size; otherwise, simple random sampling is used. Random route procedures are used to select sampled households. Unless an outright refusal occurs, interviewers make up to three attempts to survey the sampled household. To increase the probability of contact and completion, attempts are made at different times of the day and, where possible, on different days. If an interview cannot be obtained at the initial sampled household, a simple substitution method is used. Respondents are randomly selected within the selected households by means of the Kish grid. In economies where cultural restrictions dictate gender matching, respondents are randomly selected through the Kish grid from among all eligible adults of the interviewer's gender.

In economies where telephone interviewing is employed, random digit dialing or a nationally representative list of phone numbers is used. In most economies where cell phone penetration is high, a dual sampling frame is used. Random selection of respondents is achieved by using either the latest birthday or Kish grid method. At least three attempts are made to reach a person in each household, spread over different days and times of day.

The sample size in India was 3,000 individuals.

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

The questionnaire was designed by the World Bank, in conjunction with a Technical Advisory Board composed of leading academics, practitioners, and policy makers in the field of financial inclusion. The Bill and Melinda Gates Foundation and Gallup Inc. also provided valuable input. The questionnaire was piloted in multiple countries, using focus groups, cognitive interviews, and field testing. The questionnaire is available in 142 languages upon request.

Questions on cash withdrawals, saving using an informal savings club or person outside the family, domestic remittances, school fees, and agricultural payments are only asked in developing economies and few other selected countries. The question on mobile money accounts was only asked in economies that were part of the Mobile Money for the Unbanked (MMU) database of the GSMA at the time the interviews were being held.

Sampling error estimates

Estimates of standard errors (which account for sampling error) vary by country and indicator. For country-specific margins of error, please refer to the Methodology section and corresponding table in Asli Demirguc-Kunt, Leora Klapper, Dorothe Singer, and Peter Van Oudheusden, “The Global Findex Database 2014: Measuring Financial Inclusion around the World.” Policy Research Working Paper 7255, World Bank, Washington, D.C.

This dataset is about books. It has 3 rows and is filtered where the book subjects is Money-India. It features 9 columns including author, publication date, language, and book publisher.

Demonetization of all the Rs.500 and Rs.1000 denomination banknotes is an attempt to curb black money, fake notes and to achieve other ancillary objectives. Numerous debates have been held over this move and various pros and cons of demonetization have come into picture. Against these backdrops, in this paper it is tried to find out the immediate effect of demonetization on the FMCG sector. It is likely that immediate cash crunch arising out of demonetization is likely to impact the sales and other performance of FMCG Companies. Analysis is made on the quarterly performance on the selected FMCG companies and annual reports are thoroughly scrutinized to find out the views of the companies concerned on demonetization and its effect. The content analysis is made by searching for terms Like “demonetization”, cash-crunch cash shortage etc. The analysis reveals that most of the sample companies have made some disclosure in the annual report on demonetization. Our analysis reveals that for 7 companies there is absolute negative growth in sales and for 4 companies sales growth is lower as compared to sales growth of corresponding quarter of previous year in respect of December end quarter.

Money Supply M3 in India increased to 279345.46 INR Billion in the week ending May 30 from 276509.09 INR Billion two weeks before. This dataset provides - India Money Supply M3 - actual values, historical data, forecast, chart, statistics, economic calendar and news.

The Reserve Bank of India (RBI) is the central banking institution of India, responsible for the issuance and supply of the Indian Rupee and the regulation of the money market. In the context of data and information, RBI plays a pivotal role by regularly publishing a plethora of economic indicators, reports, and research. This includes data on interest rates, inflation, foreign exchange reserves, banking statistics, monetary and credit policies, and more. Researchers, policymakers, investors, and the general public rely on the RBI's data for insights into the health and direction of the Indian economy. Additionally, its publications often serve as authoritative sources for financial analysis, economic forecasting, and policy formulation in India.

Broad money (% of GDP) in India was reported at 82.1 % in 2021, according to the World Bank collection of development indicators, compiled from officially recognized sources. India - Broad money (% of GDP) - actual values, historical data, forecasts and projections were sourced from the World Bank on June of 2025.

Abstract

Financial inclusion is critical in reducing poverty and achieving inclusive economic growth. When people can participate in the financial system, they are better able to start and expand businesses, invest in their children’s education, and absorb financial shocks. Yet prior to 2011, little was known about the extent of financial inclusion and the degree to which such groups as the poor, women, and rural residents were excluded from formal financial systems.

By collecting detailed indicators about how adults around the world manage their day-to-day finances, the Global Findex allows policy makers, researchers, businesses, and development practitioners to track how the use of financial services has changed over time. The database can also be used to identify gaps in access to the formal financial system and design policies to expand financial inclusion.

Geographic coverage

Sample excludes Northeast states and remote islands, representing less than 10% of the population.

Analysis unit

Individuals

Universe

The target population is the civilian, non-institutionalized population 15 years and above.

Kind of data

Observation data/ratings [obs]

Sampling procedure

The indicators in the 2017 Global Findex database are drawn from survey data covering almost 150,000 people in 144 economies-representing more than 97 percent of the world’s population (see table A.1 of the Global Findex Database 2017 Report for a list of the economies included). The survey was carried out over the 2017 calendar year by Gallup, Inc., as part of its Gallup World Poll, which since 2005 has annually conducted surveys of approximately 1,000 people in each of more than 160 economies and in over 150 languages, using randomly selected, nationally representative samples. The target population is the entire civilian, noninstitutionalized population age 15 and above. Interview procedure Surveys are conducted face to face in economies where telephone coverage represents less than 80 percent of the population or where this is the customary methodology. In most economies the fieldwork is completed in two to four weeks.

In economies where face-to-face surveys are conducted, the first stage of sampling is the identification of primary sampling units. These units are stratified by population size, geography, or both, and clustering is achieved through one or more stages of sampling. Where population information is available, sample selection is based on probabilities proportional to population size; otherwise, simple random sampling is used. Random route procedures are used to select sampled households. Unless an outright refusal occurs, interviewers make up to three attempts to survey the sampled household. To increase the probability of contact and completion, attempts are made at different times of the day and, where possible, on different days. If an interview cannot be obtained at the initial sampled household, a simple substitution method is used.

Respondents are randomly selected within the selected households. Each eligible household member is listed and the handheld survey device randomly selects the household member to be interviewed. For paper surveys, the Kish grid method is used to select the respondent. In economies where cultural restrictions dictate gender matching, respondents are randomly selected from among all eligible adults of the interviewer’s gender.

In economies where telephone interviewing is employed, random digit dialing or a nationally representative list of phone numbers is used. In most economies where cell phone penetration is high, a dual sampling frame is used. Random selection of respondents is achieved by using either the latest birthday or household enumeration method. At least three attempts are made to reach a person in each household, spread over different days and times of day.

The sample size was 3000.

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

The questionnaire was designed by the World Bank, in conjunction with a Technical Advisory Board composed of leading academics, practitioners, and policy makers in the field of financial inclusion. The Bill and Melinda Gates Foundation and Gallup Inc. also provided valuable input. The questionnaire was piloted in multiple countries, using focus groups, cognitive interviews, and field testing. The questionnaire is available in more than 140 languages upon request.

Questions on cash on delivery, saving using an informal savings club or person outside the family, domestic remittances, and agricultural payments are only asked in developing economies and few other selected countries. The question on mobile money accounts was only asked in economies that were part of the Mobile Money for the Unbanked (MMU) database of the GSMA at the time the interviews were being held.

Sampling error estimates

Estimates of standard errors (which account for sampling error) vary by country and indicator. For country-specific margins of error, please refer to the Methodology section and corresponding table in Demirgüç-Kunt, Asli, Leora Klapper, Dorothe Singer, Saniya Ansar, and Jake Hess. 2018. The Global Findex Database 2017: Measuring Financial Inclusion and the Fintech Revolution. Washington, DC: World Bank

Consumer spending across India amounted to 24.57 trillion rupees by the end of the second quarter of 2024. It reached an all-time high during the fourth quarter of 2023. What is consumer spending? Consumer spending refers to the total money spent on final goods and services by individuals and households in an economy. It is an important metric that directly impacts the GDP of a country. Items that qualify as consumer spending include durable and nondurable goods and services. Various factors such as debt held by consumers, wages, supply and demand, taxes, and government-based economic stimulus can impact consumer spending in a country. Positive consumer outlook in India India’s consumer spending reflects a positive outlook with renewed consumer confidence post-COVID. Its consumer market is set to become one of the largest in the world as the number of middle- to high-income households rises with increasing amounts of disposable incomes. The country’s young demographic is also considered a driving force for increased consumer spending. Consumer electronics such as smartphones, laptops, and gaming consoles were the preferred items among Indian holiday shoppers in 2023.

Indian Electoral Bonds Data

This dataset presents a detailed overview of the expenditures made by various companies through Indian Electoral Bonds since 2019. Electoral bonds, introduced by the Government of India in 2018, were aimed to be a mechanism for political funding. The Government of India had introduced them for transparency in the electoral process, however, the Supreme Court of India declared them unconstitutional on February 15, 2024, on the grounds of bypassing the right to information of the citizens of India.

Context: The dataset emerges amidst significant legal and regulatory developments surrounding electoral bonds in India. The Election Commission of India (ECI), in compliance with orders from the Supreme Court (SC), mandated the State Bank of India (SBI) to furnish details regarding electoral bonds. Following the SC's ruling declaring the 2018 scheme unconstitutional, the SBI was directed to disclose electoral bond data to the ECI by March 15, 2024. This dataset encapsulates the information disclosed by the ECI on its website.

Contents: 1. Purchaser Details: This section includes information on the purchasers of electoral bonds, encompassing names, dates of purchase, and denominations. 2. Political Party Beneficiaries: It delineates the political parties receiving donations through electoral bonds, featuring details such as dates, denominations, and parties encashing the bonds. 3. Financial Metrics: The dataset encompasses financial aspects of electoral bond transactions, offering insights into the amounts donated through bonds of varying denominations (₹1 lakh, ₹10 lakh, and ₹1 crore).

Significance: This dataset holds paramount importance in shedding light on the intersection of corporate interests and political funding in India. By revealing the identities of donors, their associated companies, and the recipient political parties, it facilitates a deeper understanding of political financing dynamics. It is to be noted that the data of the money spent by a party is not mapped to the data of the money received by the corresponding political party, the reason for this, as stated by the SBI, was that these data were maintained in two physical silos and the SBI needed time till June 30, 2024, to map them (one month after the National elections 2024 in India).

Implications: Stakeholders ranging from policymakers and researchers to journalists and civil society can leverage this dataset to scrutinize the flow of funds within the political landscape. It provides a foundation for assessing the influence of corporate entities on electoral processes and policy formulation.

Key Insights: The dataset showcases contributions from diverse corporate entities, including prominent names like Megha Engineering and Infrastructure, Future Gaming and Hotel Services (Lottery Martin), Sun Pharma, Lakshmi Mittal, Sula Wine, and DLF Commercial Developers. Furthermore, it highlights major political parties such as the BJP, Congress, AITMC, BRS, AIDMK, TDP, YSR Congress, AAP, SP, and JD(U) as recipients of electoral bond donations.

Usage: Researchers can utilize this dataset to conduct in-depth analyses on patterns of political funding, donor preferences, and the impact of electoral bonds on democratic processes. Additionally, journalists can employ this data to produce investigative reports, enhancing public awareness and accountability.

Ethical Considerations: While this dataset provides valuable insights, it raises ethical questions regarding the influence of corporate interests on democratic institutions. It underscores the importance of robust regulatory frameworks and transparency measures to safeguard the integrity of electoral processes.

Conclusion: This Kaggle dataset serves as a valuable resource for elucidating the intricacies of political financing in India. By fostering transparency and accountability, it empowers stakeholders to engage in informed discussions and advocate for reforms aimed at strengthening democratic governance.

India M3: Net FX Assets of Banking Sector: RBI data was reported at 28,712,710.000 INR mn in Oct 2018. This records a decrease from the previous number of 28,988,190.000 INR mn for Sep 2018. India M3: Net FX Assets of Banking Sector: RBI data is updated monthly, averaging 357,070.000 INR mn from Mar 1951 (Median) to Oct 2018, with 595 observations. The data reached an all-time high of 28,988,190.000 INR mn in Sep 2018 and a record low of 590.000 INR mn in Mar 1966. India M3: Net FX Assets of Banking Sector: RBI data remains active status in CEIC and is reported by Reserve Bank of India. The data is categorized under Global Database’s India – Table IN.KAA001: Money Supply.