The benchmark interest rate in the United States was last recorded at 4.50 percent. This dataset provides the latest reported value for - United States Fed Funds Rate - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

The benchmark interest rate in Sweden was last recorded at 2 percent. This dataset provides the latest reported value for - Sweden Interest Rate - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

30 Year Mortgage Rate in the United States decreased to 6.63 percent in August 7 from 6.72 percent in the previous week. This dataset includes a chart with historical data for the United States 30 Year Mortgage Rate.

Fixed 30-year mortgage rates in the United States averaged 6.77 percent in the week ending August 1 of 2025. This dataset provides the latest reported value for - United States MBA 30-Yr Mortgage Rate - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

The benchmark interest rate in Japan was last recorded at 0.50 percent. This dataset provides - Japan Interest Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

FocusEconomics' economic data is provided by official state statistical reporting agencies as well as our global network of leading banks, think tanks and consultancies. Our datasets provide not only historical data, but also Consensus Forecasts and individual forecasts from the aformentioned global network of economic analysts. This includes the latest forecasts as well as historical forecasts going back to 2010. Our global network consists of over 1000 world-renowned economic analysts from which we calculate our Consensus Forecasts. In this specific dataset you will find economic data for Japan Interest Rate.

The benchmark interest rate in Brazil was last recorded at 15 percent. This dataset provides - Brazil Interest Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Senegal SN: Interest Rate Spread data was reported at -1.630 % pa in 2016. This records an increase from the previous number of -1.844 % pa for 2015. Senegal SN: Interest Rate Spread data is updated yearly, averaging -3.008 % pa from Dec 2005 (Median) to 2016, with 12 observations. The data reached an all-time high of -0.558 % pa in 2005 and a record low of -3.602 % pa in 2009. Senegal SN: Interest Rate Spread data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Senegal – Table SN.World Bank.WDI: Interest Rates. Interest rate spread is the interest rate charged by banks on loans to private sector customers minus the interest rate paid by commercial or similar banks for demand, time, or savings deposits. The terms and conditions attached to these rates differ by country, however, limiting their comparability.; ; International Monetary Fund, International Financial Statistics and data files.; Median;

Iran IR: Lending Interest Rate data was reported at 18.000 % pa in 2016. This records an increase from the previous number of 14.210 % pa for 2015. Iran IR: Lending Interest Rate data is updated yearly, averaging 12.000 % pa from Dec 2004 (Median) to 2016, with 13 observations. The data reached an all-time high of 18.000 % pa in 2016 and a record low of 11.000 % pa in 2013. Iran IR: Lending Interest Rate data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Iran – Table IR.World Bank.WDI: Interest Rates. Lending rate is the bank rate that usually meets the short- and medium-term financing needs of the private sector. This rate is normally differentiated according to creditworthiness of borrowers and objectives of financing. The terms and conditions attached to these rates differ by country, however, limiting their comparability.; ; International Monetary Fund, International Financial Statistics and data files.; ;

This table contains data described by the following dimensions (Not all combinations are available): Geography (1 items: Canada ...).

Indonesia Banking Survey: Loan Interest Rate: Whole Year Estimation: in USD: Investment data was reported at 6.566 % in Mar 2025. This records an increase from the previous number of 6.446 % for Dec 2024. Indonesia Banking Survey: Loan Interest Rate: Whole Year Estimation: in USD: Investment data is updated quarterly, averaging 6.330 % from Mar 2012 (Median) to Mar 2025, with 53 observations. The data reached an all-time high of 6.961 % in Sep 2023 and a record low of 4.454 % in Mar 2022. Indonesia Banking Survey: Loan Interest Rate: Whole Year Estimation: in USD: Investment data remains active status in CEIC and is reported by Bank Indonesia. The data is categorized under Indonesia Premium Database’s Business and Economic Survey – Table ID.SE003: Banking Survey: Interest Rate. [COVID-19-IMPACT]

Context

Have you ever wondered how lenders use various factors such as credit score, annual income, the loan amount approved, tenure, debt-to-income ratio etc. and select your interest rates?

The process, defined as ‘risk-based pricing’, uses a sophisticated algorithm that leverages different determining factors of a loan applicant. Selection of significant factors will help develop a prediction algorithm which can estimate loan interest rates based on clients’ information. On one hand, knowing the factors will help consumers and borrowers to increase their credit worthiness and place themselves in a better position to negotiate for getting a lower interest rate. On the other hand, this will help lending companies to get an immediate fixed interest rate estimation based on clients information. Here, your goal is to use a training dataset to predict the loan rate category (1 / 2 / 3) that will be assigned to each loan in our test set.

You can use any combination of the features in the dataset to make your loan rate category predictions. Some features will be easier to use than others.

Acknowledgements

https://datahack.analyticsvidhya.com/contest/janatahack-machine-learning-for-banking/True/#ProblemStatement

Analysis of ‘ Zillow Housing Aspirations Report’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/yamqwe/zillow-housing-aspirations-reporte on 13 February 2022.

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

About this dataset

Additional Data Products

Product: Zillow Housing Aspirations Report

Date: April 2017

Definitions

Home Types and Housing Stock

• All Homes: Zillow defines all homes as single-family, condominium and co-operative homes with a county record. Unless specified, all series cover this segment of the housing stock.
• Condo/Co-op: Condominium and co-operative homes.
• Multifamily 5+ units: Units in buildings with 5 or more housing units, that are not a condominiums or co-ops.
• Duplex/Triplex: Housing units in buildings with 2 or 3 housing units.

Additional Data Products

• Zillow Home Value Forecast (ZHVF): The ZHVF is the one-year forecast of the ZHVI. Our forecast methodology is methodology post.
• Zillow creates our negative equity data using our own data in conjunction with data received through our partnership with TransUnion, a leading credit bureau. We match estimated home values against actual outstanding home-related debt amounts provided by TransUnion. To read more about how we calculate our negative equity metrics, please see our here.
• Cash Buyers: The share of homes in a given area purchased without financing/in cash. To read about how we calculate our cash buyer data, please see our research brief.
• Mortgage Affordability, Rental Affordability, Price-to-Income Ratio, Historical ZHVI, Historical ZHVI and Houshold Income are calculated as a part of Zillow’s quarterly Affordability Indices. To calculate mortgage affordability, we first calculate the mortgage payment for the median-valued home in a metropolitan area by using the metro-level Zillow Home Value Index for a given quarter and the 30-year fixed mortgage interest rate during that time period, provided by the Freddie Mac Primary Mortgage Market Survey (based on a 20 percent down payment). Then, we consider what portion of the monthly median household income (U.S. Census) goes toward this monthly mortgage payment. Median household income is available with a lag. For quarters where median income is not available from the U.S. Census Bureau, we calculate future quarters of median household income by estimating it using the Bureau of Labor Statistics’ Employment Cost Index. The affordability forecast is calculated similarly to the current affordability index but uses the one year Zillow Home Value Forecast instead of the current Zillow Home Value Index and a specified interest rate in lieu of PMMS. It also assumes a 20 percent down payment. We calculate rent affordability similarly to mortgage affordability; however we use the Zillow Rent Index, which tracks the monthly median rent in particular geographical regions, to capture rental prices. Rents are chained back in time by using U.S. Census Bureau American Community Survey data from 2006 to the start of the Zillow Rent Index, and Decennial Census for all other years.
• The mortgage rate series is the average mortgage rate quoted on Zillow Mortgages for a 30-year, fixed-rate mortgage in 15-minute increments during business hours, 6:00 AM to 5:00 PM Pacific. It does not include quotes for jumbo loans, FHA loans, VA loans, loans with mortgage insurance or quotes to consumers with credit scores below 720. Federal holidays are excluded. The jumbo mortgage rate series is the average jumbo mortgage rate quoted on Zillow Mortgages for a 30-year, fixed-rate, jumbo mortgage in one-hour increments during business hours, 6:00 AM to 5:00 PM Pacific Time. It does not include quotes to consumers with credit scores below 720. Traditional federal holidays and hours with insufficient sample sizes are excluded.

About Zillow Data (and Terms of Use Information)

• Zillow is in the process of transitioning some data sources with the goal of producing published data that is more comprehensive, reliable, accurate and timely. As this new data is incorporated, the publication of select metrics may be delayed or temporarily suspended. We look forward to resuming our usual publication schedule for all of our established datasets as soon as possible, and we apologize for any inconvenience. Thank you for your patience and understanding.
• All data accessed and downloaded from this page is free for public use by consumers, media, analysts, academics etc., consistent with our published Terms of Use. Proper and clear attribution of all data to Zillow is required.
• For other data requests or inquiries for Zillow Real Estate Research, contact us here.
• All files are time series unless noted otherwise.
• To download all Zillow metrics for specific levels of geography, click here.
• To download a crosswalk between Zillow regions and federally defined regions for counties and metro areas, click here.
• Unless otherwise noted, all series cover single-family residences, condominiums and co-op homes only.

Source: https://www.zillow.com/research/data/

This dataset was created by Zillow Data and contains around 200 samples along with Unnamed: 1, Unnamed: 0, technical information and other features such as: - Unnamed: 1 - Unnamed: 0 - and more.

How to use this dataset

• Analyze Unnamed: 1 in relation to Unnamed: 0
• Study the influence of Unnamed: 1 on Unnamed: 0
• More datasets

Acknowledgements

If you use this dataset in your research, please credit Zillow Data

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

The benchmark interest rate in Norway was last recorded at 4.25 percent. This dataset provides the latest reported value for - Norway Interest Rate - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

FocusEconomics' economic data is provided by official state statistical reporting agencies as well as our global network of leading banks, think tanks and consultancies. Our datasets provide not only historical data, but also Consensus Forecasts and individual forecasts from the aformentioned global network of economic analysts. This includes the latest forecasts as well as historical forecasts going back to 2010. Our global network consists of over 1000 world-renowned economic analysts from which we calculate our Consensus Forecasts. In this specific dataset you will find economic data for South Africa Interest Rate.

Nepal NP: Real Interest Rate data was reported at -6.207 % pa in 2010. This records an increase from the previous number of -6.823 % pa for 2009. Nepal NP: Real Interest Rate data is updated yearly, averaging 3.657 % pa from Dec 1975 (Median) to 2010, with 29 observations. The data reached an all-time high of 18.214 % pa in 1977 and a record low of -12.173 % pa in 1975. Nepal NP: Real Interest Rate data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Nepal – Table NP.World Bank.WDI: Interest Rates. Real interest rate is the lending interest rate adjusted for inflation as measured by the GDP deflator. The terms and conditions attached to lending rates differ by country, however, limiting their comparability.; ; International Monetary Fund, International Financial Statistics and data files using World Bank data on the GDP deflator.; ;

Monetary policy is generally regarded as a central element in the attempts of policy makers to attenuate business-cycle fluctuations. According to the New Keynesian paradigm, central banks are able to stimulate or depress aggregate demand in the short run by adjusting their nominal interest rate targets. The effects of interest rate changes on aggregate consumption, the largest component of aggregate demand, are well understood in the context of this paradigm, on which the canonical "workhorse'' model used in monetary policy analysis is grounded. A key feature of the model is that aggregate consumption is fully described by the amount of goods consumed by a representative household. A decline in the policy rate for instance implies that the real interest rate declines, the representative household saves less and hence increase its demand for consumption. At the same time, general equilibrium effects let labour income grow causing consumption to increase further. However, the mechanism outlined above ignores a considerable amount of empirically-observed heterogeneity among households. For example, households with a higher earnings elasticity to interest rate changes benefit more from a rate cut than those with a lower elasticity; households with large debt positions are at a relative advantage over households with large bond holdings; and households with low exposure to inflation are relatively better off than those holding a sizeable amount of nominal assets. As a result, the contribution to the aggregate consumption response differs substantially across households, implying that monetary expansions and tightenings produce relative "winners'' and relative "losers''. The aim of the project laid out in this proposal is to give a disaggregated account of the heterogeneous effects of monetary-policy induced interest rate changes on household consumption and a detailed analysis of the channels underlying them. Additionally, it seeks to draw conclusions about the determinants of the strength of the transmission mechanism of monetary policy. To do so, it relies on a large panel comprising detailed data from the universe of all households residing in Norway between 1993 and 2015 supplemented with additional micro-data provided by the European Commission. I will be assisted by two project partners, Pascal Paul who is a member of the Research Department of the Federal Reserve Bank of San Francisco and Martin Holm who is affiliated with the Research Unit of Statistics Norway and the University of Oslo. In addition, I would like to collaborate with and help train a doctoral student based at the University of Lausanne on this project. Existing empirical studies of the consumption response to monetary policy at the micro level rely on survey data. Therefore, they are subject to a number of severe data limitations. The surveys employed typically have either no or only a short panel dimension, suffer from attrition, include only limited information on income and wealth, are top-coded, and contain a significant amount of measurement error. The administrative data set provided to us by Statistics Norway suffers from none of these issues, implying that we are in a unique position to evaluate the household-level effects of policy rate changes. In a first step, we use forecasts published by the Norwegian central bank to derive monetary policy shocks that are robust to the simultaneity problem inherent in the identification of the effects of monetary policy following Romer and Romer (2004). We then confront the micro-data with the estimated shocks to study the consumption response along different segments of the income and wealth distribution and to test the importance of heterogeneity in labour earnings, financial income, liquid assets, inflation exposure and interest rate exposure among others. The findings will be of high relevance as they will not only allow us to evaluate channels hypothesised in the analytical literature, improve our understanding of the monetary policy transmission mechanism and its distributional consequences but also serve as a benchmark for structural models built both by theorists and practitioners.

The benchmark interest rate in Germany was last recorded at 4.50 percent. This dataset provides - Germany Interest Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

The benchmark interest rate in Mexico was last recorded at 7.75 percent. This dataset provides - Mexico Interest Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

The benchmark interest rate In the Euro Area was last recorded at 2.15 percent. This dataset provides - Euro Area Interest Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.