In 2024, the national debt of India amounted to around 3.16 trillion U.S. dollars. Projections show an upward trend, with a significant increase each year. Honor thy national debtNational debt, also called government debt or public debt, is money owed by the federal government. It can be divided into internal debt, (which is owed to lenders in the country) and external debt (which is owed to foreign lenders). National debt is created and increased by using government bonds, for example, or by borrowing money from other nations due to financial struggles (well-known case in point: Greece). A quite complex issue, national debt is expected to be paid back in accordance with certain regulations overseen by the Bank for International Settlements (BIS), a financial organization owned by central banks. India’s debt is rising, but so is its economic growthIndia’s liabilities have increased significantly, and forecasts show no end in sight. While India is a fast-growing economy and considered one of the main emerging economies, the so-called BRIC countries, India has been investing and borrowing money from commercial banks as well as several non-banking finance companies, and its national debt today makes up almost 70 percent of its GDP. Luckily, even though the national debt is forecast to increase, this share of GDP is predicted to decrease, as is the trade deficit in the long run, despite a significant jump back into the red in 2017.

Key information about India Government Debt: % of GDP

• India Government debt accounted for 57.2 % of the country's Nominal GDP in Sep 2024, compared with the ratio of 57.1 % in the previous quarter.
• India government debt to GDP ratio data is updated quarterly, available from Mar 2012 to Sep 2024.
• The data reached an all-time high of 58.8 % in Sep 2023 and a record low of 44.6 % in Dec 2018.

CEIC calculates quarterly Government Debt as % of Nominal GDP from quarterly Government Debt and rolling sum of quarterly Nominal GDP. The Ministry of Finance provides Government Debt in local currency. Ministry of Statistics and Programme Implementation provides Nominal GDP in local currency. Government Debt covers Central Government only.


Related information about India Government Debt: % of GDP

• In the latest reports, India National Government Debt reached 2,144.6 USD bn in Sep 2024.
• The country's Nominal GDP reached 873.7 USD bn in Mar 2023.

The statistic shows the national debt in India from 2020 to 2023 in relation to gross domestic product (GDP), with projections up until 2030. In 2023, the national debt of India amounted to about 81.23 percent of the gross domestic product. India’s economy on the rise India is one of the most populous countries in the world, and although a large share of inhabitants are living below the poverty line – or probably due to this fact –, the country’s economy is growing steadily. India’s GDP growth is expected to remain steady at more than 7 percent for the next few years, which is almost double that of the global GDP, and both GDP and GDP per capita are expected to increase significantly. Almost half of India’s workforce is employed in the agricultural sector, but services and industry share the other half quite equally. India’s GDP is mostly generated by the services sector, which includes transport, retailing, and offering services in the hospitality and tourism industry. India’s trade balance has been in the red for a decade now, but seems to recover slowly. A trade deficit usually means that a country’s import costs are higher than the amount of money generated with exporting goods. India’s imports could not be compensated for by the country’s exports, as imports have been consistently, even if only slightly, higher over the years both in terms of volume and value. Still, all signs point to India’s economy growing and thriving, reducing India’s debt (as seen above) and unemployment rate, enabling the inhabitants to create a better life for themselves.

India CCIL: Outstanding Government Debt: State Development Loans data was reported at 60,906,220.000 INR mn in Feb 2025. This records an increase from the previous number of 60,002,550.000 INR mn for Jan 2025. India CCIL: Outstanding Government Debt: State Development Loans data is updated monthly, averaging 12,730,780.000 INR mn from Apr 2005 (Median) to Feb 2025, with 239 observations. The data reached an all-time high of 60,906,220.000 INR mn in Feb 2025 and a record low of 2,180,756.500 INR mn in Apr 2005. India CCIL: Outstanding Government Debt: State Development Loans data remains active status in CEIC and is reported by The Clearing Corporation of India Limited. The data is categorized under India Premium Database’s Financial Market – Table IN.ZD011: The Clearing Corporation of India Limited (CCIL): Outstanding Government Debt. State Development Loans do not include Power Bonds

The statistic shows Japan's national debt from 2020 to 2023 in relation to gross domestic product (GDP), with projections up until 2030. In 2023, the national debt of Japan amounted to about 239.97 percent of the gross domestic product. An eye on Japan’s national debt Japan’s national debt ranks first among countries with the highest debt levels in the world, far surpassing the debt levels of Greece - which ranks number two - whose financial crisis has been in the spotlight recently. Italy is third, followed by Jamaica, Lebanon and Enritrea. Currently, Japan’s national debt amounts more than a thousand trillion yen and the country’s debt is predicted to keep rising for the foreseeable future, albeit only slightly. Japan’s national debt is not without consequence for the global economy, because the country claims the fourth-largest share in global gross domestic product. Therefore, the effects on the global economy would and could have a much greater global impact than that of a country such as Greece - considering its share of the global economy adjusted for purchase power parity was less than 0.29 percent in 2011. The debt levels of China, the United States and India should also be watched closely as they together make up the largest share of global GDP. At the moment, Japan’s inflation rate is among the lowest in the world, but as Japan attempts to reduce its national debt, this could change.

As of December 2024, Japan held United States treasury securities totaling about 1.06 trillion U.S. dollars. Foreign holders of United States treasury debt According to the Federal Reserve and U.S. Department of the Treasury, foreign countries held a total of 8.5 trillion U.S. dollars in U.S. treasury securities as of December 2024. Of the total held by foreign countries, Japan and Mainland China held the greatest portions, with China holding 759 billion U.S. dollars in U.S. securities. The U.S. public debt In 2023, the United States had a total public national debt of 33.2 trillion U.S. dollars, an amount that has been rising steadily, particularly since 2008. In 2023, the total interest expense on debt held by the public of the United States reached 678 billion U.S. dollars, while 197 billion U.S. dollars in interest expense were intra governmental debt holdings. Total outlays of the U.S. government were 6.1 trillion U.S. dollars in 2023. By 2029, spending is projected to reach 8.3 trillion U.S. dollars.

The state of *********** recorded the highest number of farmer suicides in financial year 2023. The southern state of Karnataka ranked second with over ***** deaths due to suicide during the same time. Debt and bankruptcy were among the leading reasons for these numbers. Overall farmer debt was estimated to be at around *** million Indian rupees in 2021.

Abstract

The main objective of the All India Debt and Investment Survey (AIDIS) is to generate reliable estimates on assets, liabilities and capital expenditure of the household sector. The survey provides the details of household liabilities required for the formulation of credit policy of financial institutions and planning for development.

The required information was collected from the same set of sample households in two visits to each sample. The information to be collected in the second visit to the household was considerably less than that collected in the first visit. In view of this uneven work-load in the two visits, it was decided to extend the survey period of the first visit to eight months - from January to August 1992 - and to reduce the survey period of the second visit to four months - from September to December 1992. As a result, the households which have been visited in the first two months of the first visit were revisited in the first month of the second visit and so on. To reduce the fatigue of the respondent, it was decided that unlike in the 37th round, the sample households in this round would be selected separately for schedules 18.1 and 18.2 in the rural sector. Since the land and livestock holdings were likely to be small in most cases, it was decided to survey the same set of sample households both for schedules 18.1 and 18.2 in the urban sector.

The position in regard to the assets and liabilities of the sample households was required to be collected with reference to a fixed date, namely, as on the 30th June1991. There was a time lag between the reference date and the survey date in the first visit varying from household to household within the range of maximum period of 14 months. To derive the above, therefore, it was decided to collect information on assets and liabilities as on the date of survey and the transactions relating to the said assets and liabilities carried out during the period intervening the date of reference and the date of survey.

Broadly, the following information has been collected in this round of survey:- (i) the asset and the liability position of the households

(ii) the amount of capital expenditure on (a) residential plots, houses or buildings, (b) farm business and (c) non-farm business, incurred by the household during the reference period of agricultural year 1991-22.

(iii) acquisition, disposal and loss of assets during July 1991 to June 1992.The assets owned by the households have been classified into three categories, namely, (a) physical assets contributing to capital formation (b) financial assets and (c) durable household assets. Besides collection of information for deriving the asset and liability position of the households as on 30.6.91, provisions have also been made to collect data on the transactions of physical, financial and household durable assets and also on the cash borrowings and repayments made during the agricultural year 1991-92.

Geographic coverage

The 48th Round was planned to cover the whole of Indian Union except

(i) Ladakh and Kargil districts of Jammu & Kashmir, (ii) 768 interior villages of Nagaland (out of a total of 1119 villages ) located beyond 5 kms. of a bus route, (iii) 172 villages in Andaman & Nicobar Islands (out of a total of 520 villages) which are inaccessible throughout the year. However, the survey could not be conducted in certain districts of Jammu & Kashmir viz. Anantnag, Pulwana, Srinagar, Badgam, Baramula and Kupwara, and the district of Amritsar in Punjab due to unfavourable field conditions.

Analysis unit

Randomly selected households based on sampling procedure and members of the household

Universe

The survey used the interview method of data collection from a sample of randomly selected households and members of the household.

Kind of data

Sample survey data [ssd]

Sampling procedure

Sample Design A stratified two-stage sampling design was adopted for the survey with the first stage units as census villages for rural areas and the Urban Frame Survey blocks for urban areas. Households formed the second statge units in both rural and urban areas.

Sampling frame for first stage units(FSU's): In the rural sector, the sampling frame in most of the strata was the 1981 census list of villages. However, in Assam, where the 1981 census was not undertaken, and in a few districts of other states, where the available list as per 1981 census was incomplete, the 1971 census list of villages was used. In the urban sector, the sampling frames used in most cases were the lists of NSS Urban Frame Survey (UFS) blocks. However, the 1991 census house listing enumeration blocks were considered as the sampling units for some of the new towns declared as urban areas in the 1991 population census.

Stratification: Each state/union territory (u.t.) was divided into one or more agro-economic regions by grouping contiguous districts which are similar with respect to population density and crop pattern. In Gujarat, however, some districts were subdivided for the purpose of region formation on the basis of location of dry areas and the distribution of tribal population in the state. The total number of regions formed in the India as whole was 78.

In the rural sector, within each region, each district with a rural population of less than 1.8 million according to the 1981 census formed a single basic stratum. Districts with larger population were divided into two or more strata, depending on population, by grouping contiguous tehsils, similar as far as possible in respect of rural population density and crop pattern. In Gujarat, however, in the case of districts extending over more than one region, the portion of a district falling in each region constituted a separate stratum even if the rural population of the district as a whole was less than 1.8 million. Further, in Assam, the strata formed for the earlier NSS rounds on the basis of 1971 census rural population exactly in the above manner, but with a cut-off of 1.5 million population, were retained as the strata for rural sampling.

In the urban sector, strata were formed, again within NSS regions, on the basis of 1981 (1991 in some of the new towns) census population of towns. Each city with a population 10 lakhs or more formed a separate stratum by itself. The remaining towns of each region were grouped to form three different strata on the basis of 1981 (1991 in a few cases) census population.

Allocation of sample: A total all-India sample of 6,812 first stage units (4,328 villages and 2,484 urban blocks) - determined on the basis of investigator strength in different states/u.t.'s and the expected workload per investigator - was initially allocated to the states/u.t's in proportion to central field staff available. The sample thus obtained for each state/u.t. was then allocated to its rural and urban sectors considering the relative sizes of the rural and urban population with almost double weightage being given for the urban sector. Within each sector of state/u.t., the allotted sample size was re-allocated to the different strata in proportion to the stratum population. All allocations were adjusted so that the sample size for a stratum was at least a multiple of 4 for the rural and urban sectors separately. This was done to accomplish equal sized samples in each sub-sample and sub-round. The only exception was Daman & Diu for which the first stage rural sample comprised 2 villages only.

Selection of first stage units: The selection of sample villages was PPS (with replacement) with population as the size variable, in the form of two independent subsamples. The sample blocks were selected by simple random sampling without replacement, also in the form of two independent subsamples.

Selection of hamlet-groups/sub-blocks: Large villages and blocks were divided into a suitable number of hamlet-groups and sub-blocks, respectively, having more or less equal population content. Two hamlet-groups were then selected from large villages, whereas only one sub-block was selected from the large blocks. The hamlet-groups were selected circular systematically and the sub-block with equal probability.

Selection of households: Two different procedures of selection of households were used for the rural and urban sectors. Different procedures for the two sectors were necessary, since in the rural sector schedules of enquiry for LHS survey and Debt & Investment survey were required to be canvassed in two separate sets of sample households, while in the urban sector, both the schedules were to be canvassed in the same set of sample households.

In the rural sector, nine households were selected from each sample village/selected hamlet groups. For selecting a sample of nine households, each sample village/hamlet group was sub-divided into 7 AIDIS sub-strata on the joint consideration of "land possessed" and "indebtedness status" of the households; first, all the households of the sample village/selected hamlet groups were divided into four LHS sub-strata by area of land possessed by them. Households possessing either no land or land less than 0.005 acre were grouped in substratum 1. The rest of the households were then arranged in ascending order by area of land possessed and classified into three substrata, 2, 3 and 4, such that the total area of land possessed by the households in each of the 3 sub-strata was nearly the same. Each of the LHS sub-strata 1 and 2 was further divided into "indebted" and "not indebted" groups to form AIDIS sub-stratum 1 to 4. AIDIS sub-strata 5 to 7 are formed by first merging LHS substrata numbers 3 and 4 and then sub-divided by the merged group into 3 classes, viz., (a) indebted to institutional agencies with or without being

Of the major developed economies, Japan had the highest debt to equity ratio for financial corporations, reaching *** in 2022. The United Kingdom had the second-highest debt to equity ratio with *** percent while the United States had the lowest with only *** percent. The debt to equity ratio is a measure of whether companies finance their activities with equity or debt. It is calculated by dividing the total outstanding debt of all financial corporations by the market value of those companies' shares. A ratio of 2.5, for example, means that outstanding debt is 2.5 times larger than the market value of the financial sector's equity.

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.

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.

As of July 18, 2025, the major economy with the highest yield on 10-year government bonds was Turkey, with a yield of ** percent. This is due to the risks investors take when investing in Turkey, notably due to high inflation rates potentially eradicating any profits made when using a foreign currency to investing in securities denominated in Turkish lira. Of the major developed economies, United Kingdom had one the highest yield on 10-year government bonds at this time with **** percent, while Switzerland had the lowest at **** percent. How does inflation influence the yields of government bonds? Inflation reduces purchasing power over time. Due to this, investors seek higher returns to offset the anticipated decrease in purchasing power resulting from rapid price rises. In countries with high inflation, government bond yields often incorporate investor expectations and risk premiums, resulting in comparatively higher rates offered by these bonds. Why are government bond rates significant? Government bond rates are an important indicator of financial markets, serving as a benchmark for borrowing costs, interest rates, and investor sentiment. They affect the cost of government borrowing, influence the price of various financial instruments, and serve as a reflection of expectations regarding inflation and economic growth. For instance, in financial analysis and investing, people often use the 10-year U.S. government bond rates as a proxy for the longer-term risk-free rate.