The benchmark interest rate in the United States was last recorded at 4.25 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 the United Kingdom was last recorded at 4 percent. This dataset provides - United Kingdom Interest Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

30 Year Mortgage Rate in the United States decreased to 6.30 percent in October 9 from 6.34 percent in the previous week. This dataset includes a chart with historical data for the United States 30 Year Mortgage Rate.

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.

The benchmark interest rate in Canada was last recorded at 2.50 percent. This dataset provides - Canada Interest Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

The benchmark interest rate in Turkey was last recorded at 40.50 percent. This dataset provides the latest reported value for - Turkey Interest Rate - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

The Treasury Loans to Government Agencies table represents the specific maturities for the Treasury Loans to Government Agencies rate changes from the previous month to the current month for a set maturity time frame.

The benchmark interest rate in Sweden was last recorded at 1.75 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.

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.

This dataset examines financial inclusion and bank stability in Ethiopia, containing panel data from 17 commercial banks over the period 2015-2023. In 2015, there were 17 commercial banks in Ethiopia but to maintain confidentiality, the names of commercial banks have been anonymized and are referred to by generic labels: 1, 2, 3, 4..., and 17. This process allows the dataset to be analyzed and shared openly in support of reproducibility and transparency in research.VariablesBank Stability (ZS): Computed using the Z-score to measure stability.Financial Inclusion Index (IFI): Developed using two-stage Principal Component Analysis (PCA) with 10 conventional and 5 digital indicators.Loan to Deposit Ratio (LDR): Computed based on the loan to deposit ratio.Provision to Loan (PL): Computes the loan loss provision ratio.Natural Logarithm of Total Assets (lnTA): Logarithmic form of total assets.Capital Adequacy Ratio (CAR): Computed by Tier-1 capital and Tier-2 capital divided by risk-weighted assets.Income Diversification (IND): Computed based on the non-interest income to total income ratio.Operational Efficiency Management (EF): Measured using Data Envelopment Analysis (DEA) with five input variables (salary and benefits, provisions, general expenses, branches, and deposits) and two output variables (net interest income and non-interest income).Real Lending Interest Rate (RLIR): Inflation-adjusted interest rate.GDP Growth Rate (GDP): Annual percentage change in GDP.This dataset provides comprehensive insights into the relationships between financial inclusion and bank stability, supporting future research and policy formulation.

This table contains 71 series, with data starting from 1934 (not all combinations necessarily have data for all years). This table contains data described by the following dimensions (Not all combinations are available): Geography (1 items: Canada ...), Rates (71 items: Bank rate; last Tuesday or last Thursday; Bank rate; Chartered bank administered interest rates - prime business; Chartered bank - consumer loan rate ...).

This table contains 102 series, with data starting from 2013, and some select series starting from 2016. This table contains data described by the following dimensions (Not all combinations are available): Geography (1 item: Canada), Components (51 items: Total, funds advanced, residential mortgages, insured; Variable rate, insured; Fixed rate, insured, less than 1 year; Fixed rate, insured, from 1 to less than 3 years; ...), and Unit of measure (2 items: Dollars; Interest rate). For additional clarification on the component dimension, please visit the OSFI website for the Report on New and Existing Lending.

The benchmark interest rate in South Africa was last recorded at 7 percent. This dataset provides - South Africa Interest Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

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

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.

The benchmark interest rate in India was last recorded at 5.50 percent. This dataset provides - India Interest Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

The benchmark interest rate in Taiwan was last recorded at 2 percent. This dataset provides the latest reported value for - Taiwan Interest 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 Poland was last recorded at 4.50 percent. This dataset provides - Poland Interest Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

The benchmark interest rate in China was last recorded at 3 percent. This dataset provides the latest reported value for - China Interest 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 Switzerland was last recorded at 0 percent. This dataset provides - Switzerland Interest Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.