Households Debt in the United States decreased to 69.20 percent of GDP in the fourth quarter of 2024 from 70.50 percent of GDP in the third quarter of 2024. This dataset provides - United States Households Debt To Gdp- actual values, historical data, forecast, chart, statistics, economic calendar and news.

Total outstanding debt of the U.S. government reported daily. Includes a breakout of intragovernmental holdings (federal debt held by U.S. government) and debt held by the public (federal debt held by entities outside the U.S. government).

Private Debt to GDP in the United States decreased to 142 percent in 2024 from 147.50 percent in 2023. United States Private Debt to GDP - values, historical data, forecasts and news - updated on June of 2025.

Households Debt in France decreased to 95.35 percent of gross income in 2023 from 101.84 percent in 2022. This dataset provides - France Households Debt To Income- actual values, historical data, forecast, chart, statistics, economic calendar and news.

Content

More details about each file are in the individual file descriptions.

Context

This is a dataset from the Federal Reserve Bank of St. Louis hosted by the Federal Reserve Economic Database (FRED). FRED has a data platform found here and they update their information according to the frequency that the data updates. Explore the Federal Reserve Bank of St. Louis using Kaggle and all of the data sources available through the St. Louis Fed organization page!

• Update Frequency: This dataset is updated daily.

Acknowledgements

This dataset is maintained using FRED's API and Kaggle's API.

Cover photo by Noah Silliman on Unsplash
Unsplash Images are distributed under a unique Unsplash License.

Statistics on student debt, including the average debt at graduation, the percentage of graduates who owed large debt at graduation and the percentage of graduates with debt who had paid it off at the time of the interview, are presented by the province of study and the level of study. Estimates are available at five-year intervals.

This dataset provides values for HOUSEHOLDS DEBT TO INCOME reported in several countries. The data includes current values, previous releases, historical highs and record lows, release frequency, reported unit and currency.

Graph and download economic data for Federal Debt: Total Public Debt (GFDEBTN) from Q1 1966 to Q1 2025 about public, debt, federal, government, and USA.

Households Debt in China decreased to 60 percent of GDP in the fourth quarter of 2024 from 60.10 percent of GDP in the third quarter of 2024. This dataset provides - China Households Debt To Gdp- actual values, historical data, forecast, chart, statistics, economic calendar and news.

Debt service ratios, interest and obligated principal payments on debt, and related statistics for households, Canada.

Households Debt in India increased to 41.90 percent of GDP in the fourth quarter of 2024 from 41.30 percent of GDP in the third quarter of 2024. This dataset provides - India Households Debt To Gdp- actual values, historical data, forecast, chart, statistics, economic calendar and news.

Analysis of ‘Macro-economic indicators - Indebtedness’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from http://data.europa.eu/88u/dataset/ecb-macro-economic-indicators-indebtedness on 07 January 2022.

--- Dataset description provided by original source is as follows ---

Indebtedness refers to government debt-to-GDP ratio, government deficit-to-GDP ratio, households' debt-to-gross disposable income ratio and non-financial corporations' debt-to-gross domestic product ratio.

Government debt-to-GDP ratio refers to the Maastricht criteria. The government debt statistics used are those used in the context of the excessive deficit procedure. (Financial stocks at nominal value, percentage points, not seasonally or working day adjusted). The last two years presented in the graphs are based on European Commission forecasts (Directorate-General for Economic and Financial Affairs). The reference value set by the Maastricht criteria is 60%.

Government deficit-to-GDP ratio refers to the Maastricht criteria. The government deficit statistics include settlements under swaps (non-financial flows, current prices, percentage points, not seasonally or working day adjusted). The last two years presented in the graphs are based on European Commission forecasts (Directorate-General for Economic and Financial Affairs). The reference value for the budget deficit under the Stability and Growth Pact is 3%.

Households' debt-to-gross disposable income ratio. Gross disposable income is adjusted for the change in net equity of households in pension fund reserves (non-consolidated, current prices, percentage points, not seasonally or working day adjusted).

Non-financial corporations' debt-to-gross domestic product ratio. The statistics are taken from the national accounts statistics. Debt includes pension reserve liabilities and excludes financial derivatives owing to a lack of comparability across countries (non-consolidated, market prices, percentage points, not seasonally or working day adjusted).

--- Original source retains full ownership of the source dataset ---

Households Debt in Lithuania increased to 22.16 percent of GDP in the fourth quarter of 2024 from 21.89 percent of GDP in the third quarter of 2024. This dataset provides - Lithuania Households Debt To Gdp- actual values, historical data, forecast, chart, statistics, economic calendar and news.

Households Debt in Slovakia decreased to 68.94 percent of gross income in 2024 from 69.21 percent in 2023. This dataset provides - Slovakia Households Debt To Income- actual values, historical data, forecast, chart, statistics, economic calendar and news.

Households Debt in Sweden decreased to 83.40 percent of GDP in the fourth quarter of 2024 from 84 percent of GDP in the third quarter of 2024. This dataset provides - Sweden Households Debt To Gdp- actual values, historical data, forecast, chart, statistics, economic calendar and news.

http://debtpro.co/credit-card-debt-consolidation-bad-credit/ The International Bank for Reconstruction and Development (IBRD) loans are public and publicly guaranteed debt extended by the World Bank Group. IBRD loans are made to, or guaranteed by, countries that are members of IBRD. IBRD may also make loans to IFC. IBRD lends at market rates. Data are in U.S. dollars calculated using historical rates. This dataset contains the latest available snapshot of the Statement of Loans. The World Bank complies with all sanctions applicable to World Bank transactions.

DESCRIPTION

A banking institution requires actionable insights into mortgage-backed securities, geographic business investment, and real estate analysis. The mortgage bank would like to identify potential monthly mortgage expenses for each region based on monthly family income and rental of the real estate. A statistical model needs to be created to predict the potential demand in dollars amount of loan for each of the region in the USA. Also, there is a need to create a dashboard which would refresh periodically post data retrieval from the agencies. The dashboard must demonstrate relationships and trends for the key metrics as follows: number of loans, average rental income, monthly mortgage and owner’s cost, family income vs mortgage cost comparison across different regions. The metrics described here do not limit the dashboard to these few. Dataset Description

Variables

Description Second mortgage Households with a second mortgage statistics Home equity Households with a home equity loan statistics Debt Households with any type of debt statistics Mortgage Costs Statistics regarding mortgage payments, home equity loans, utilities, and property taxes Home Owner Costs Sum of utilities, and property taxes statistics Gross Rent Contract rent plus the estimated average monthly cost of utility features High school Graduation High school graduation statistics Population Demographics Population demographics statistics Age Demographics Age demographic statistics Household Income Total income of people residing in the household Family Income Total income of people related to the householder Project Task: Week 1

Data Import and Preparation:

Import data.

Figure out the primary key and look for the requirement of indexing.

Gauge the fill rate of the variables and devise plans for missing value treatment. Please explain explicitly the reason for the treatment chosen for each variable.

Exploratory Data Analysis (EDA):

Perform debt analysis. You may take the following steps:

Explore the top 2,500 locations where the percentage of households with a second mortgage is the highest and percent ownership is above 10 percent. Visualize using geo-map. You may keep the upper limit for the percent of households with a second mortgage to 50 percent

Use the following bad debt equation:

Bad Debt = P (Second Mortgage ∩ Home Equity Loan) Bad Debt = second_mortgage + home_equity - home_equity_second_mortgage Create pie charts to show overall debt and bad debt

Create Box and whisker plot and analyze the distribution for 2nd mortgage, home equity, good debt, and bad debt for different cities

Create a collated income distribution chart for family income, house hold income, and remaining income

Perform EDA and come out with insights into population density and age. You may have to derive new fields (make sure to weight averages for accurate measurements):

Use pop and ALand variables to create a new field called population density

Use male_age_median, female_age_median, male_pop, and female_pop to create a new field called median age

Visualize the findings using appropriate chart type

Create bins for population into a new variable by selecting appropriate class interval so that the number of categories don’t exceed 5 for the ease of analysis.

Analyze the married, separated, and divorced population for these population brackets

Visualize using appropriate chart type

Please detail your observations for rent as a percentage of income at an overall level, and for different states.

Perform correlation analysis for all the relevant variables by creating a heatmap. Describe your findings.

Project Task: Week 2

Data Pre-processing:

The economic multivariate data has a significant number of measured variables. The goal is to find where the measured variables depend on a number of smaller unobserved common factors or latent variables.

Each variable is assumed to be dependent upon a linear combination of the common factors, and the coefficients are known as loadings. Each measured variable also includes a component due to independent random variability, known as “specific variance” because it is specific to one variable. Obtain the common factors and then plot the loadings. Use factor analysis to find latent variables in our dataset and gain insight into the linear relationships in the data.

  Following are the list of latent variables:

Highschool graduation rates

Median population age

Second mortgage statistics

Percent own

Bad debt expense

Data Modeling :

Build a linear Regression model to predict the total monthly expenditure for home mortgages loan.

  Please refer deplotment_RE.xlsx. Column hc_mortgage_mean is predicted variable. This is the mean monthly mortgage and owner costs of specified geographical location.

  Note: Exclude loans from prediction model which have NaN (Not a Numb...

Graph and download economic data for Personal Saving Rate (PSAVERT) from Jan 1959 to Apr 2025 about savings, personal, rate, and USA.

Households Debt in Mexico increased to 16.70 percent of GDP in the fourth quarter of 2024 from 16.50 percent of GDP in the third quarter of 2024. This dataset provides - Mexico Households Debt To Gdp- actual values, historical data, forecast, chart, statistics, economic calendar and news.

This table contains 58320 series, with data for years 1999 - 2016 (not all combinations necessarily have data for all years). This table contains data described by the following dimensions (Not all combinations are available): Geography (20 items: Canada; Atlantic; Newfoundland and Labrador; Prince Edward Island; ...); Assets and debts (27 items: Total assets; Private pension assets; Registered Retirement Savings Plans (RRSPs), Registered Retirement Income Funds (RRIFs), Locked-in Retirement Accounts (LIRAs) and other; Employer-sponsored Registered Pension Plans (EPPs); ...); Net worth quintiles (6 items: Total, all net worth quintiles; Lowest net worth quintile; Second net worth quintile; Middle net worth quintile; ...); Statistics (6 items: Total values; Percentage of total assets or total debts; Number holding asset or debt; Percentage holding asset or debt; ...); Confidence intervals (3 items: Estimate; Lower bound of a 95% confidence interval; Upper bound of a 95% confidence interval).