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.

Gross-Profit Time Series for Chemung Financial Corp. Chemung Financial Corporation operates as a bank holding company for Chemung Canal Trust Company that provides a range of banking, financing, fiduciary, and other financial services. The company provides demand, savings, and time deposits; non-interest and interest-bearing checking accounts; and insured money market deposits. It also offers commercial and agricultural loans comprising loans to small to mid-sized businesses; commercial and residential mortgage loans; and consumer loans, including home equity lines of credit and home equity term loans, as well as automobile loans. In addition, the company provides interest rate swaps, letters of credit, employee benefit plans, insurance products, mutual fund, brokerage, and tax preparation services. Further, it offers guardian, custodian, trustee, investment, pension, estate planning, and employee benefit administrative services, as well as acts as an agent for pension, profit-sharing, and other employee benefit trusts. Chemung Financial Corporation was founded in 1833 and is based in Elmira, New York.

The Industrial Revenue Bond program (IRB) provides access to tax-exempt financing to help businesses and non-profit organizations renovate and build new construction, make tenant improvements, and purchase capital by securing interest rates up 4% lower than a traditional commercial loan. IRBs can be used to finance, refinance, and reimburse the costs of acquiring, constructing, restoring, rehabilitating, expanding, improving, equipping, or furnishing real property and related subordinate facilities. More than $9.5 billion has been issued through Washington, DC's IRB program since 1994.

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Context

45 financial metrics and ratios of every company included in the Nasdaq-100 stock market index (as of 09/2021) for the last five fiscal years. Some metrics or ratios might not be calculated, depending on the company's profitability [...].

Inspiration

The dataset offers a vast variety of possibilities for data exploration, data preparation and visualization, classification or clustering of the different companies, and the prediction of future developments of certain metrics and ratios.

Covered Metrics and Ratios

Besides the stock symbol, the company name and the respective GICS sector and GICS subsector classification, the datasets comprises information about (1) Asset Turnover, (2) Buyback Yield, (3) CAPEX to Revenue, (4) Cash Ratio, (5) Cash to Debt, (6) COGS to Revenue, (7) Beneish M-Score, (8) Altman Z-Score, (9) Current Ratio, (10) Days Inventory, (11) Debt to Equity, (12) Debt to Assets, (13) Debt to EBITDA, (14) Debt to Revenue, (15) E10 (by Prof. Robert Shiller), (16) Effective Interest Rate, (17) Equity to Assets, (18) Enterprise Value to EBIT, (19) Enterprise Value to EBITDA, (20) Enterprise Value to Revenue, (21) Financial Distress, (22) Financial Strength, (23) Joel Greenblatt Earnings Yield (by Joel Greenblatt), (24) Free Float Percentage, (25) Piotroski F-Score, (26) Goodwill to Assets, (27) Gross Profit to Assets, (28) Interest Coverage, (29) Inventory Turnover, (30) Inventory to Revenue, (31) Liabilities to Assets, (32) Long-term Debt to Assets, (33) Price-to-Book-Ratio, (34) Price-to-Earnings-Ratio, (35) Price-to-Earnings-Ratio (Non-Recurring Items), (36) Price-Earnings-Growth-Ratio, (37) Price-to-Free-Cashflow, (38) Price-to-Operating-Cashflow, (39) Predictability, (40) Profitability, (41) Rate of Return, (42) Scaled Net Operating Assets, (43) Year-over-Year EBITDA Growth, (44) Year-over-Year EPS Growth, (45) Year-over-Year Revenue Growth

Note, that the dates defining a fiscal year may vary from company to company.

Acknowledgements

The contents are provided by wikipedia.de and gurufocus.com from where the data was scraped.

The dataset, named "Tax Complexity and Economic Development Dataset," explores the relationship between tax complexity and the economic development of nations. The data covers the years 2016 to 2022 and comprises the following columns:

Country: Name of the country. Year: Year of the data. Tax Complexity Index: Index measuring the overall complexity of a country's tax system. Tax Complexity Index Rank: Rank of the country based on the Tax Complexity Index. Tax Code Complexity: Complexity inherent in different regulations of the tax code. Tax Code Complexity Rank: Rank of the country based on Tax Code Complexity. Tax Framework Complexity: Complexity arising from features and processes of a tax system. Tax Framework Complexity Rank: Rank of the country based on Tax Framework Complexity. Additional Taxes Complexity: Complexity of taxes levied on multinational corporations (MNCs) in addition to corporate income taxes. Additional Taxes Rank: Rank of the country based on Additional Taxes Complexity. (Alternative) Minimum Tax Complexity: Separate income tax regulations to ensure that an MNC pays at least a minimum amount of taxes. (Alternative) Minimum Tax Rank: Rank of the country based on (Alternative) Minimum Tax Complexity. Capital Gains Complexity: Complexity related to capital gains realized by an MNC on the disposal of non-inventory assets. Capital Gains Rank: Rank of the country based on Capital Gains Complexity. CFC-Rules Complexity: Regulations to combat profit shifting to companies in low- or no-tax jurisdictions controlled by an MNC. CFC-Rules Rank: Rank of the country based on CFC-Rules Complexity. Corporate Reorganization Complexity: Complexity related to the change in the structure or ownership of an MNC through reorganization. Corporate Reorganization Rank: Rank of the country based on Corporate Reorganization Complexity. Depreciation Complexity: Deductions for allocating the costs of assets over their useful lives. Depreciation Rank: Rank of the country based on Depreciation Complexity. Dividends Complexity: Complexity of cash dividends received or paid by an MNC. Dividends Rank: Rank of the country based on Dividends Complexity. General Anti-Avoidance Complexity: Broad regulations denying the benefit of a transaction designed to avoid taxes. General Anti-Avoidance Rank: Rank of the country based on General Anti-Avoidance Complexity. Group Treatment Complexity: Regime allowing the grouping of profits and losses of associated companies. Group Treatment Rank: Rank of the country based on Group Treatment Complexity. Interest Complexity: Complexity of interest payments received or paid by an MNC. Interest Rank: Rank of the country based on Interest Complexity. Investment Incentives Complexity: Measures designed to encourage investment and promote innovation. Investment Incentives Rank: Rank of the country based on Investment Incentives Complexity. Loss Offset Complexity: Form of relief for ordinary losses incurred. Loss Offset Rank: Rank of the country based on Loss Offset Complexity. Royalties Complexity: Complexity of payments for the use of intellectual property. Royalties Rank: Rank of the country based on Royalties Complexity. Statutory Tax Rate Complexity: Complexity of the tax rate that applies to MNCs' determined taxable income. Statutory Tax Rate Rank: Rank of the country based on Statutory Tax Rate Complexity. Transfer Pricing Complexity: Regulations to prevent prices from being charged to a subsidiary to excessively reduce taxable income. Transfer Pricing Rank: Rank of the country based on Transfer Pricing Complexity. Guidance Complexity: Guidance provided by the tax authority or other laws to resolve uncertain tax issues. Guidance Rank: Rank of the country based on Guidance Complexity. Enactment Complexity: Complexity of the formal process of how a tax proposal becomes law. Enactment Rank: Rank of the country based on Enactment Complexity. Payment & Filing Complexity: Process of preparing and filing a tax return as well as paying taxes. Payment & Filing Rank: Rank of the country based on Payment & Filing Complexity. Audits Complexity: Complexity of the examination and verification of a tax return carried out by the tax authority. Audits Rank: Rank of the country based on Audits Complexity. Appeals Complexity: Complexity of the process of challenging a tax assessment. Appeals Rank: Rank of the country based on Appeals Complexity. Country Code: Code representing the country. Taxes on income, profits and capital gains (% of total taxes): Percentage of total taxes levied on income, profits, and capital gains. GDP growth (annual %): Annual percentage growth rate of GDP at market price...

CL: Total Tax Rate: % of Profit data was reported at 34.000 % in 2019. This stayed constant from the previous number of 34.000 % for 2018. CL: Total Tax Rate: % of Profit data is updated yearly, averaging 27.700 % from Dec 2005 (Median) to 2019, with 15 observations. The data reached an all-time high of 34.000 % in 2019 and a record low of 24.500 % in 2011. CL: Total Tax Rate: % of Profit data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Chile – Table CL.World Bank.WDI: Company Statistics. Total tax rate measures the amount of taxes and mandatory contributions payable by businesses after accounting for allowable deductions and exemptions as a share of commercial profits. Taxes withheld (such as personal income tax) or collected and remitted to tax authorities (such as value added taxes, sales taxes or goods and service taxes) are excluded.;World Bank, Doing Business project (http://www.doingbusiness.org/). NOTE: Doing Business has been discontinued as of 9/16/2021. For more information: https://bit.ly/3CLCbme;Unweighted average;Data are presented for the survey year instead of publication year.

Success.ai’s Company Funding Data Solutions offer businesses access to over 28 million verified company profiles, delivering detailed insights into private company data across multiple industries. Our solution includes firmographic data and business location data for companies of all sizes, from large enterprises to small businesses. Whether you're seeking small business contact data or company funding data, Success.ai’s company data solutions empower businesses with the accuracy and depth they need to drive B2B sales, marketing, and research initiatives.

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View data of the S&P 500, an index of the stocks of 500 leading companies in the US economy, which provides a gauge of the U.S. equity market.

On the occasion of the 50th anniversary of the currency reform and of the introduction of the German D-mark on 20th June 1948, the German Bundesbank – in its function as central bank and bank of issue of the Federal Republic of Germany – presented long series of monetary statistics in 1998. In approximately 1,400 data charts, extensive information about the development of the German finance and banking industry, the capital market, and the foreign trade relations are given. In total, approximately 25,000 time series about the following core subjects were collected: general overviews of banking statistics, bank of issue, credit institutions, minimum reserves, interest rates, statistics of exchange rates, capital market, public finances, foreign trade, macroeconomic capital finance accounts and annual accounts of West German companies. Factual classification of the tables in HISTAT: A. Selected data regarding the economic development A.1 Monetary development A.2 Population and labour market A.3 Macroeconomic production and demand A.4 Prices and wages A.5 Distribution of the national income and incomes of the private households B. Foreign trade (currently not completed in HISTAT; access to the subjects B2, B3, B4, B7 see below) B1. Foreign debts and liabilities of domestic companies B.2 Foreign debts and liabilities of the credit institutions B.3 Foreign cross ownerships of German companies B.4 Regional balances of payment B.5 State of assets compared to other countries B.6 Balance of payments B.7 Additional specifications regarding the balance of payments B.8 Foreign payments by the German Bundesbank Any data including a differentiation of countries (EU countries, other industrialised countries, some developing countries, countries of the off-shore finance centres, OPEC countries, reform countries) are currently only available by placing an order with the ZHSF Data Service (ordering address see below) C. General overviews of bank statistics C.1 Consolidated balance of the banking system, assets C.2 Consolidated balance of the banking system, liabilities C.3 Cash circulation C.4 Development of money supply in connection with the balance C.5 Money demand of the Central Bank D. Exchange rate statistics D.1 External value indeces D.2 Exchange rates at the Frankfurt stock exchange D.3 Values of the ECU D.4 Values of the extra educational law E. Macroeconomic capital finance account E1. Domestic financial sectors E2. Domestic non-financial sectors E3. Other countries F. Annual accounts of West German companies F.1 All German companies F.2 Building industry F.3 Clothing trade F.4 Chemical industry F.5 Retail industry (incl. automobile trade and service stations) F.6 Electrical engineering F.7 Power and water supply F.8 Food industry F.9 Glas industry, ceramics, processing of stones and earths F.10 Wholesale trade and trade negotiations F.11 Production of rubber and plastic goods F.12 Production of automobiles and automobile parts F.13 Production of metal goods F.14 Timber industry F.15 Engineering F.16 Medical, measurement, driving and control technology F.17 Metal production and metal working F.18 Paper industry F.19 Textile industry F.20 Manufacturing industry F.21 Transportation (without rail) F.22 Publishing and printing G. Capital market (currently not in HISTAT; access see below) G1. Shares of domestic issuers G2. General overviews G3. Exchange transactions, option and future business G4. Domestic capital investment companies G5. Bonds of foreign issuers G6. Bonds of domestic issuers H. Credit institutions (currently not in HISTAT; access see below) H1. Assets H2. Liabilities H3. Assets and liabilities of the foreign branches and foreign subsidiaries of domestic banks H4. Building associations H5. Deposit statistics H6. Deposits and loans H7. profit situation of the banks H8. domestic and foreign debts and liabilities H9. Circulating bearer bonds according to their terms and bank group H10. Loans H11. Savings deposits and savings certificates H12. Savings business turnover according to bank group and endorsed disposals of non-bank financial companies H13. equity stocks and shares I. Minimum reserves (currently not registered in HISTAT; access see below) I.1 Overview I.2 Itemisation according to steps of progression (from March 1977) I3. Itemisation according to reserve classes (until February 1977) I1.1 Reserve stockpiles according to bank group, obligatory reserve liabilities I1.2. Reserve stockpiles according to bank group, Reserve debits I.2 Reserve ratios J. Central bank (currently not registered in HISTAT; access see below) J.1 Assets J.2 Liabilities K. Public finances K.1 Financial development of the public budgeting K1. Public debts L. Interest rates L.1 Money market rates L1. Bank interest rates (currently not registered in HISTAT; access see below).

This dataset provides a comprehensive view of a company’s financial and operational performance over the period from 2019 to 2023. It includes key metrics such as revenue, net profit, total comprehensive income, total assets, total equity, customer base, and indicators for return on equity (ROE) and return on assets (ROA). Additionally, the dataset contains a dummy variable to indicate the occurrence of a significant cyber incident in 2022. Data Fields:Year: The fiscal year for the reported data.Revenue (million GBP): Total income generated from sales and other operations, measured in millions of GBP.Net Profit (million GBP): The profit after all expenses, taxes, and costs, reported in millions of GBP.Total Comprehensive Income (million GBP): A measure of company performance that includes net income and other comprehensive income, reported in millions of GBP.Total Assets (million GBP): The total value of everything the company owns, reported in millions of GBP.Total Equity (million GBP): The shareholders' equity, representing the residual interest in the assets of the company after deducting liabilities, reported in millions of GBP.Customer Base (millions): The number of customers the company serves, measured in millions.ROE (%): Return on Equity, calculated as (Net Profit / Total Equity) * 100, and expressed as a percentage.ROA (%): Return on Assets, calculated as (Net Profit / Total Assets) * 100, and expressed as a percentage.CyberIncident: A binary variable (0 or 1) indicating the occurrence of a cyber incident in the corresponding year, with ‘1’ indicating an incident and ‘0’ indicating none.Key Insights:Revenue Growth: The company has shown significant growth in revenue, particularly from 2021 onwards, reflecting a strong upward trend in business performance.Profitability: After a challenging period in 2019 and 2020, the company achieved positive net profit starting in 2021, with substantial growth by 2023.Operational Efficiency: The ROE and ROA values demonstrate an improving trend in the company’s efficiency in utilizing equity and assets to generate profits.Customer Expansion: The customer base has expanded rapidly, tripling from 10 million in 2019 to 35 million in 2023, indicating successful market penetration and customer acquisition strategies.Cyber Incident Impact: A notable cyber incident occurred in 2022, which may have influenced financial and operational metrics during that period.Potential Uses:This dataset is valuable for financial analysts, researchers, and business strategists interested in understanding the financial trajectory, operational efficiency, and market growth of a company over a five-year period. It also provides insights into the impact of cyber incidents on company performance.

This release presents the main results from an analysis of the profitability and resilience of farms in England using data from the Farm Business Survey. Six measures have been examined; liabilities, net worth, gearing ratios, liquidity, net interest payments as a proportion of Farm Business Income and Return on Capital Employed (ROCE). Link to main notice: https://www.gov.uk/government/collections/farm-business-survey#documents Survey details The Farm Business Survey (FBS) is an annual survey providing information on the financial position and physical and economic performance of farm businesses in England. The sample of around 1,900 farm businesses covers all regions of England and all types of farming with the data being collected by face to face interview with the farmer. Results are weighted to represent the whole population of farm businesses that have at least 25 thousand Euros of standard output as recorded in the annual June Survey of Agriculture and Horticulture. In 2012 there were just over 56 thousand farm businesses meeting this criteria. The data used for this analysis is from only those farms present in the Farm Business Survey (FBS) for 2010/11 to 2012/13. Those entering or leaving the survey in this period have been excluded. The sub sample consists of around 1490 farms. For further information about the Farm Business Survey please see: https://www.gov.uk/government/organisations/department-for-environment-food-rural-affairs/series/farm-business-survey Data analysis The results from the FBS relate to farms which have a standard output of at least 25,000 Euros. Initial weights are applied to the FBS records based on the inverse sampling fraction for each design stratum (farm type by farm size). These weights are then adjusted (calibration weighting) so that they can produce unbiased estimators of a number of different target variables. All data in this release is based on farms present in the FBS for 2010/11 to 2012/13 and that have complete returns on their assets and liabilities. Those entering or leaving the survey in this period have been excluded. This sub sample consists of around 1490 farms. The results for this subsample have been reweighted using a method that preserves marginal totals for populations according to farm type and farm size groups. As such, farm population totals for other classifications (e.g. regions) will not be in-line with results using the main FBS weights, nor will any results produced for variables derived from the rest of the FBS (e.g. farm business income). Measures represent a three year average from 2010-2013, presented in 2012/2013 prices (uprated according to RPI inflation). This helps to stabilise the fluctuations in income that can significantly change the financial position of a farm from year to year. ? Accuracy and reliability of the results We show 95% confidence intervals against the results. These show the range of values that may apply to the figures. They mean that we are 95% confident that this range contains the true value. They are calculated as the standard errors (se) multiplied by 1.96 to give the 95% confidence interval (95% CI). The standard errors only give an indication of the sampling error. They do not reflect any other sources of survey errors, such as non-response bias. For the Farm Business Survey, the confidence limits shown are appropriate for comparing groups within the same year only; they should not be used for comparing with previous years since they do not allow for the fact that many of the same farms will have contributed to the Farm Business Survey in both years. We have also shown error bars on the figures in this notice. These error bars represent the 95% confidence intervals (as defined above). For the FBS, where figures are based on less than 5 observations these have been suppressed to prevent disclosure and where they are based on less than 15 observations these have been highlighted in the tables. Availability of results Defra statistical notices can be viewed on the Food and Farming Statistics pages on the Defra website at https://www.gov.uk/government/organisations/department-for-environment-food-rural-affairs/about/statistics. This site also shows details of future publications, with pre-announced dates. Definitions Mean The mean (average) is found by adding up the weighted variable of interest (e.g. liabilities or net worth) for each individual farm in the population for analysis and dividing the result by the corresponding weighted number of farms. In this report average is usually taken to refer to the mean. Percentiles These are the values which divide the population for analysis, when ranked by an output variable (e.g. ROCE or net worth), into 100 equal-sized groups. For example, twenty five per cent of the population would have incomes below the 25th percentile. Median The median divides the population, when ranked by an output variable, into two equal sized groups. The median of the whole population is the same as the 50th percentile. Farm Type Where reference is made to the type of farm in this document, this refers to the ‘robust type’, which is a standardised farm classification system. Farm Sizes Farm sizes are based on the estimated labour requirements for the business, rather than its land area. The farm size bands used within the detailed results tables which accompany this publication are shown in the table below. Standard Labour Requirement (SLR) is defined as the theoretical number of workers required each year to run a business, based on its cropping and livestock activities. Farm size Definition Spare & Part time Less than 1 SLR Small 1 to less than 2 SLR Medium 2 to less than 3 SLR Large 3 to less than 5 SLR Very Large 5 or more SLR Assets Assets include milk and livestock quotas, as well as land, buildings (including the farm house), breeding livestock, and machinery and equipment. For tenanted farmers, assets can include farm buildings, cottages, quotas, etc., where these are owned by the occupier. Personal possessions (e.g. jewellery, furniture, and possibly private cash) are not included. Net worth Net worth represents the residual claim or interest of the owner in the business. It is the balance sheet value of assets available to the owner of the business after all other claims against these assets have been met. Net worth takes total liabilities from total assets, including tenant type capital and land. This describes the wealth of a farm if all of their liabilities were called in.? Liabilities Liabilities are the total debt (short and long term) of the farm business including monies owed. It includes mortgages, long term loans and monies owed for hire purchase, leasing and overdrafts. Tenant type capital Tenant type capital comprises assets normally provided by tenants and includes livestock, machinery, crops and produce in store, stocks of bought and home-grown feeding stuffs and fodder, seeds, fertilisers, pesticides, medicines, fuel and other purchased materials, work in progress (tillages or cultivations), cash and other assets needed to run the business. Orchards, other permanent crops, such as soft fruit and hop gardens and glasshouses, are also generally considered to be tenant-type capital. Return on capital employed (ROCE) Return on capital employed (ROCE) is a measure of the return that a business makes from the available capital. ROCE provides a more holistic view than profit margins, focusing on efficient use of capital and low costs and allowing an equal comparison across farms of differing sizes. It is calculated as economic profit divided by capital employed. Liquidity ratio The liquidity ratio shows the ability of a farm to finance its immediate financial demands from its current assets, such as cash, savings or stock. It is calculated as current assets divided by the current liabilities of the farms. Gearing ratio The gearing ratio gives a farm’s liabilities as a proportion of its assets Farm business income (FBI) Farm Business Income (FBI) for sole traders and partnerships represents the financial return to all unpaid labour (farmers and spouses, non-principal partners and directors and their spouses and family workers) and on all their capital invested in the farm business, including land and buildings. For corporate businesses it represents the financial return on the shareholders capital invested in the farm business. Note that prior to 2008/09 directors remuneration was not deducted in the calculation of farm business income. It is used when assessing the impact of new policies or regulations on the individual farm business. Although Farm Business Income is equivalent to financial Net Profit, in practice they are likely to differ because Net Profit is derived from financial accounting principles whereas Farm Business Income is derived from management accounting principles. For example in financial accounting output stocks are usually valued at cost of production, whereas in management accounting they are usually valued at market price. In financial accounting depreciation is usually calculated at historic cost whereas in management accounting it is often calculated at replacement cost. Net Farm Income (NFI) Net Farm Income (NFI) is intended as a consistent measure of the profitability of tenant-type farming which allows farms of different business organisation, tenure and indebtedness to be compared. It represents the return to the farmer and spouse alone for their manual and managerial labour and on the tenant-type capital invested in the farm business. To represent the return to farmer and spouse alone, a notional deduction is made for any unpaid labour provided by non-principal partners and directors, their spouses and by others; this unpaid labour is valued at average local market rates for manual agricultural work. To confine the measure to the tenant-type activities and assets of the business, an imputed rent is deducted for owner-occupied land and

The Labour Force Survey provides estimates of employment and unemployment which are among the timeliest and important measures of performance of the Canadian economy. With the release of the survey results only 10 days after the completion of data collection, the LFS estimates are the first of the major monthly economic data series to be released. The Canadian Labour Force Survey was developed following the Second World War to satisfy a need for reliable and timely data on the labour market. Information was urgently required on the massive labour market changes involved in the transition from a war to a peace-time economy. The main objective of the LFS is to divide the working-age population into three mutually exclusive classifications - employed, unemployed, and not in the labour force - and to provide descriptive and explanatory data on each of these. LFS data are used to produce the well-known unemployment rate as well as other standard labour market indicators such as the employment rate and the participation rate. The LFS also provides employment estimates by industry, occupation, public and private sector, hours worked and much more, all cross-classifiable by a variety of demographic characteristics. Estimates are produced for Canada, the provinces, the territories and a large number of sub-provincial regions. For employees, wage rates, union status, job permanency and workplace size are also produced. These data are used by different levels of government for evaluation and planning of employment programs in Canada. Regional unemployment rates are used by Employment and Social Development Canada to determine eligibility, level and duration of insurance benefits for persons living within a particular employment insurance region. The data are also used by labour market analysts, economists, consultants, planners, forecasters and academics in both the private and public sector. Note: Because missing values are removed from this dataset, any form of non-response (e.g. valid skip, not stated) or don't know/refusal cannot be coded as a missing. The "Sysmiss" label in the Statistics section indicates the number of non-responding records for each variable, and the "Valid" values in the Statistics section indicate the number of responding records for each variable. The total number of records for each variable is comprised of both the sysmiss and valid values. LFS revisions: LFS estimates were previously based on the 2001 Census population estimates. These data have been adjusted to reflect 2006 Census population estimates and were revised back to 1996. The census metropolitan area (CMA) variable has been expanded from the three largest CMAs in Canada to nine. Two occupation variables based on the 2016 National Occupation Classicifcation have been reintroduced: a generic 10- category variable (NOC_10) and a detailed 40-category variable (NOC_40). A new variable on immigrant status (IMMIG) has been introduced, which distingushes between recent immigrants and established immigrants. Fourteen variables related to family and spouse/partner's labour force characteristics have been removed, as well as eight out of date variables which have been removed from the record layout.

The benchmark interest rate in Pakistan was last recorded at 11 percent. This dataset provides - Pakistan Interest Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Bank Lending Rate in Germany decreased to 4 percent in June from 4.09 percent in May of 2025. This dataset provides the latest reported value for - Germany Bank Lending 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 Philippines was last recorded at 5 percent. This dataset provides the latest reported value for - Philippines Interest Rate - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

Corporate Profits in the United States increased to 3266.20 USD Billion in the second quarter of 2025 from 3203.60 USD Billion in the first quarter of 2025. This dataset provides the latest reported value for - United States Corporate Profits - 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 Spain was last recorded at 4.50 percent. This dataset provides the latest reported value for - Spain Interest Rate - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

The Corporate Tax Rate in the United States stands at 21 percent. This dataset provides - United States Corporate Tax Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

The benchmark interest rate in the United Arab Emirates was last recorded at 4.40 percent. This dataset provides - United Arab Emirates Interest Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

The Corporate Tax Rate in France stands at 25 percent. This dataset provides the latest reported value for - France Corporate Tax Rate - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.