34 datasets found
  1. Replication dataset and calculations for PIIE Briefing 25-2 The US Revenue...

    • piie.com
    Updated Apr 22, 2025
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    Warwick J. McKibbin; Geoffrey Shuetrim (2025). Replication dataset and calculations for PIIE Briefing 25-2 The US Revenue Implications of President Trump’s 2025 Tariffs by Warwick McKibbin and Geoffrey Shuetrim (2025). [Dataset]. https://www.piie.com/publications/piie-briefings/2025/us-revenue-implications-president-trumps-2025-tariffs
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    Dataset updated
    Apr 22, 2025
    Dataset provided by
    Peterson Institute for International Economicshttp://www.piie.com/
    Authors
    Warwick J. McKibbin; Geoffrey Shuetrim
    Description

    This data package includes the underlying data to replicate the charts, tables, and calculations presented in The US Revenue Implications of President Trump’s 2025 Tariffs, PIIE Briefing 25-2.

    If you use the data, please cite as:

    McKibbin, Warwick, and Geoffrey Shuetrim. 2025. The US Revenue Implications of President Trump’s 2025 Tariffs. PIIE Briefing 25-2. Washington: Peterson Institute for International Economics.

  2. U.S. Government Revenue Collections

    • fiscaldata.treasury.gov
    csv, json, xml
    Updated Mar 13, 2021
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    U.S. DEPARTMENT OF THE TREASURY (2021). U.S. Government Revenue Collections [Dataset]. https://fiscaldata.treasury.gov/datasets/revenue-collections-management/
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    csv, xml, jsonAvailable download formats
    Dataset updated
    Mar 13, 2021
    Dataset provided by
    United States Department of the Treasuryhttps://treasury.gov/
    Authors
    U.S. DEPARTMENT OF THE TREASURY
    Time period covered
    Oct 1, 2004 - Jul 18, 2025
    Description

    Daily overview of federal revenue collections such as income tax deposits, customs duties, fees for government service, fines, and loan repayments.

  3. Replication dataset for PIIE PB 24-1, Why Trump’s tariff proposals would...

    • piie.com
    Updated May 20, 2024
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    Kimberly Clausing; Mary E. Lovely (2024). Replication dataset for PIIE PB 24-1, Why Trump’s tariff proposals would harm working Americans by Kimberly Clausing and Mary E. Lovely (2024). [Dataset]. https://www.piie.com/publications/policy-briefs/2024/why-trumps-tariff-proposals-would-harm-working-americans
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    Dataset updated
    May 20, 2024
    Dataset provided by
    Peterson Institute for International Economicshttp://www.piie.com/
    Authors
    Kimberly Clausing; Mary E. Lovely
    Area covered
    United States
    Description

    This data package includes the underlying data files to replicate the data, tables, and charts presented in Why Trump’s tariff proposals would harm working Americans, PIIE Policy Brief 24-1.

    If you use the data, please cite as: Clausing, Kimberly, and Mary E. Lovely. 2024. Why Trump’s tariff proposals would harm working Americans. PIIE Policy Brief 24-1. Washington, DC: Peterson Institute for International Economics.

  4. g

    Sales of electricity by type of tariff - Dataset - opendata Mauritius

    • data.govmu.org
    Updated Sep 30, 2024
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    (2024). Sales of electricity by type of tariff - Dataset - opendata Mauritius [Dataset]. https://data.govmu.org/dataset/sales-electricity-type-tariff
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    Dataset updated
    Sep 30, 2024
    License

    Attribution-ShareAlike 4.0 (CC BY-SA 4.0)https://creativecommons.org/licenses/by-sa/4.0/
    License information was derived automatically

    Area covered
    Mauritius
    Description

    Data shows electricity sold by type of tariff for the year 2017 to 2021

  5. Define Best Tariff for a Telecom Company

    • kaggle.com
    Updated Aug 9, 2024
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    Roman Nikiforov (2024). Define Best Tariff for a Telecom Company [Dataset]. https://www.kaggle.com/datasets/romanniki/prospective-tariff-for-a-telecom-company/discussion
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    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Aug 9, 2024
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    Roman Nikiforov
    License

    Apache License, v2.0https://www.apache.org/licenses/LICENSE-2.0
    License information was derived automatically

    Description

    Determining the Prospective Tariff for a Telecom Company

    Project Description

    You are an analyst at "Megaline," a federal mobile operator. The company offers two tariff plans to customers: "Smart" and "Ultra." To adjust the advertising budget, the commercial department wants to understand which tariff generates more revenue.

    You need to conduct a preliminary analysis of the tariffs on a small sample of customers. You have data on 500 users of "Megaline": who they are, where they are from, which tariff they use, how many calls and messages they sent in 2018. You need to analyze customer behavior and conclude which tariff is better.

    Tariff Descriptions

    "Smart" Tariff: - Monthly fee: 550 rubles - Included: 500 minutes of calls, 50 messages, and 15 GB of internet traffic - Cost of services beyond the tariff package: 1. Call minute: 3 rubles (Megaline always rounds up minutes and megabytes. If the user talked for just 1 second, it counts as a whole minute); 2. Message: 3 rubles; 3. 1 GB of internet traffic: 200 rubles.

    "Ultra" Tariff: - Monthly fee: 1950 rubles - Included: 3000 minutes of calls, 1000 messages, and 30 GB of internet traffic - Cost of services beyond the tariff package: 1. Call minute: 1 ruble; 2. Message: 1 ruble; 3. 1 GB of internet traffic: 150 rubles.

    Note: Megaline always rounds up seconds to minutes and megabytes to gigabytes. Each call is rounded up individually: even if it lasted just 1 second, it is counted as 1 minute. For web traffic, separate sessions are not counted. Instead, the total amount for the month is rounded up. If a subscriber uses 1025 megabytes in a month, they are charged for 2 gigabytes.

    Project Steps

    Step 1: Open the file with data and study the general information File paths: - /datasets/calls.csv - /datasets/internet.csv - /datasets/messages.csv - /datasets/tariffs.csv - /datasets/users.csv

    Step 2: Prepare the data - Convert data to the required types; - Find and fix errors in the data, if any. Explain what errors you found and how you fixed them. You will find calls with zero duration in the data. This is not an error: missed calls are indicated by zeros, so they do not need to be deleted.

    For each user, calculate: - Number of calls made and minutes spent per month; - Number of messages sent per month; - Amount of internet traffic used per month; - Monthly revenue from each user (subtract the free limit from the total number of calls, messages, and internet traffic; multiply the remainder by the value from the tariff plan; add the corresponding tariff plan's subscription fee).

    Step 3: Analyze the data Describe the behavior of the operator's customers based on the sample. How many minutes of calls, how many messages, and how much internet traffic do users of each tariff need per month? Calculate the average, variance, and standard deviation. Create histograms. Describe the distributions.

    Step 4: Test hypotheses - The average revenue of users of the "Ultra" and "Smart" tariffs is different; - The average revenue of users from Moscow differs from the revenue of users from other regions. Moscow is written as 'Москва'. You can put it in your value, when check the hypothesis

    Set the threshold alpha value yourself.

    Explain: - How you formulated the null and alternative hypotheses; - Which criterion you used to test the hypotheses and why.

    Step 5: Write a general conclusion

    Formatting: Perform the task in Jupyter Notebook. Fill the program code in the cells of type code, and the textual explanations in the cells of type markdown. Apply formatting and headers.

    Data Description

    Table users (user information): - user_id: unique user identifier - first_name: user's first name - last_name: user's last name - age: user's age (years) - reg_date: date of tariff connection (day, month, year) - churn_date: date of tariff discontinuation (if the value is missing, the tariff was still active at the time of data extraction) - city: user's city of residence - tariff: name of the tariff plan

    Table calls (call information): - id: unique call number - call_date: call date - duration: call duration in minutes - user_id: identifier of the user who made the call

    Table messages (message information): - id: unique message number - message_date: message date - user_id: identifier of the user who sent the message

    Table internet (internet session information): - id: unique session number - mb_used: amount of internet traffic used during the session (in megabytes) - session_date: internet session date - user_id: user identifier

    Table tariffs (tariff information): - tariff_name: tariff name - rub_monthly_fee: monthly subscription fee in rubles - minutes_included: number of call minutes included per month - `messages_included...

  6. t

    Summary of Receipts by Source, and Outlays by Function of the U.S....

    • fiscaldata.treasury.gov
    Updated Jul 13, 2020
    + more versions
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    (2020). Summary of Receipts by Source, and Outlays by Function of the U.S. Government [Dataset]. https://fiscaldata.treasury.gov/datasets/monthly-treasury-statement/
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    Dataset updated
    Jul 13, 2020
    Description

    This summary table shows, for Budget Receipts, the total amount of activity for the current month, the current fiscal year-to-date, the comparable prior period year-to-date and the budgeted amount estimated for the current fiscal year for various types of receipts (i.e. individual income tax, corporate income tax, etc.). The Budget Outlays section of the table shows the total amount of activity for the current month, the current fiscal year-to-date, the comparable prior period year-to-date and the budgeted amount estimated for the current fiscal year for functions of the federal government. The table also shows the amounts for the budget/surplus deficit categorized as listed above. This table includes total and subtotal rows that should be excluded when aggregating data. Some rows represent elements of the dataset's hierarchy, but are not assigned values. The classification_id for each of these elements can be used as the parent_id for underlying data elements to calculate their implied values. Subtotal rows are available to access this same information.

  7. g

    Water sales by tariff of subscriber - Dataset - opendata Mauritius

    • data.govmu.org
    Updated Sep 30, 2024
    + more versions
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    (2024). Water sales by tariff of subscriber - Dataset - opendata Mauritius [Dataset]. https://data.govmu.org/dataset/water-sales-tariff-subscriber
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    Dataset updated
    Sep 30, 2024
    License

    Attribution-ShareAlike 4.0 (CC BY-SA 4.0)https://creativecommons.org/licenses/by-sa/4.0/
    License information was derived automatically

    Area covered
    Mauritius
    Description

    The data shows the water sales by tariff of subscribers for island of Mauritius for the year 2016 to 2022

  8. w

    IBNET Benchmarking Database

    • wbwaterdata.org
    Updated Mar 18, 2020
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    (2020). IBNET Benchmarking Database [Dataset]. https://wbwaterdata.org/dataset/ibnet-benchmarking-database
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    Dataset updated
    Mar 18, 2020
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Data on water utilities for 151 national jurisdictions, for a range of years up to and including 2017 (year range varies greatly by country and utility) on service and utility parameters (Benchmark Database) and Tariffs for 211 juristictions (Tariffs database). Information includes cost recovery, connections, population served, financial performance, non-revenue water, residential and total supply, total production. Data can be called up by utility, by group of utility, and by comparison between utilities, including the whole (global) utility database, enabling both country and global level comparison for individual utilities. Data can be downloaded in xls format.

  9. t

    Receipts and Outlays of the U.S. Government by Month

    • fiscaldata.treasury.gov
    Updated Jul 13, 2020
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    (2020). Receipts and Outlays of the U.S. Government by Month [Dataset]. https://fiscaldata.treasury.gov/datasets/monthly-treasury-statement/
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    Dataset updated
    Jul 13, 2020
    Description

    This table shows the receipts and outlays of the United States Government by month for the current fiscal year, up to and including the current accounting month. The table also shows the total receipts and outlays for the current fiscal year-to-date and the comparable prior fiscal year-to-date. This table includes total and subtotal rows that should be excluded when aggregating data. Some rows represent elements of the dataset's hierarchy, but are not assigned values. The classification_id for each of these elements can be used as the parent_id for underlying data elements to calculate their implied values. Subtotal rows are available to access this same information.

  10. t

    Outlays of the U.S. Government

    • fiscaldata.treasury.gov
    Updated Jul 13, 2020
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    (2020). Outlays of the U.S. Government [Dataset]. https://fiscaldata.treasury.gov/datasets/monthly-treasury-statement/
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    Dataset updated
    Jul 13, 2020
    Description

    This table shows the gross outlays, applicable receipts and net outlays for the current month, current fiscal year-to-date and prior fiscal year-to-date by various agency programs accounted for in the budget of the federal government. This table includes total and subtotal rows that should be excluded when aggregating data. Some rows represent elements of the dataset's hierarchy, but are not assigned values. The classification_id for each of these elements can be used as the parent_id for underlying data elements to calculate their implied values. Subtotal rows are available to access this same information.

  11. o

    Water boards; tariffs levies

    • data.overheid.nl
    • ckan.mobidatalab.eu
    • +2more
    atom, json
    Updated May 3, 2025
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    Centraal Bureau voor de Statistiek (Rijk) (2025). Water boards; tariffs levies [Dataset]. https://data.overheid.nl/dataset/4226-water-boards--tariffs-levies
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    atom(KB), json(KB)Available download formats
    Dataset updated
    May 3, 2025
    Dataset provided by
    Centraal Bureau voor de Statistiek (Rijk)
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    This table contains data on the tariffs of the water board levies. Water boards impose these levies as remuneration for their legal tasks. The most important legal tasks are flood defense, water management (ensuring the right water level for agriculture, nature, residents) and ensuring water quality. Some water boards also manage roads and waterways. The water boards impose water system levies, road levies and non-task-related levies (till 2015) on four categories of taxpayers: residents, owners of buildings, owners of land (unbuilt) and owners of nature sites. A water board can choose to impose a separate road levy or to pay the costs of road management and maintenance from the water system levy. Water boards can apply tariff differentiation. This means that a water board can use different tariffs for the same levy for, for example, areas outside dikes and inside dikes. If this is the case, the table shows an average rate. To calculate the average rate, the total revenue is divided by the total number of units on which the charge is levied. The data included in this table have been derived from the budgets as reported by the water boards prior to each reporting year.

    Data available from: 2009

    Status of the figures: The rates for the year 2025 are provisional, rates over previous years are definitive. All provisional figures are subject to adjustments based on new or updated source material.

    Changes as of 5 March 2025: The provisional figures for 2025 have been added. The figures for 2024 are definite.

    When will new figures be published? The new figures from the water board budgets are published in the first quarter of the financial year. The figures can be adjusted on the basis of the availability of new or updated source material. In general, the adjustments are small. The adjustments are made at the moment a new annual figure is added to the series.

  12. g

    Sales of Electricity by Type of Tariff Group in Mauritius - Dataset -...

    • data.govmu.org
    Updated Sep 30, 2024
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    (2024). Sales of Electricity by Type of Tariff Group in Mauritius - Dataset - opendata Mauritius [Dataset]. https://data.govmu.org/dataset/sales-electricity-type-tariff-group-mauritius
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    Dataset updated
    Sep 30, 2024
    License

    Attribution-ShareAlike 4.0 (CC BY-SA 4.0)https://creativecommons.org/licenses/by-sa/4.0/
    License information was derived automatically

    Area covered
    Mauritius
    Description

    Sales of Electricity by Type of Tariff Group for the year 1990 to 2019 in Mauritius

  13. T

    United States Government Budget

    • tradingeconomics.com
    • es.tradingeconomics.com
    • +13more
    csv, excel, json, xml
    Updated Jun 11, 2025
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    TRADING ECONOMICS (2025). United States Government Budget [Dataset]. https://tradingeconomics.com/united-states/government-budget-value
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    csv, excel, json, xmlAvailable download formats
    Dataset updated
    Jun 11, 2025
    Dataset authored and provided by
    TRADING ECONOMICS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Jan 31, 1954 - Jun 30, 2025
    Area covered
    United States
    Description

    The United States recorded a government budget surplus of 27000 USD Million in June of 2025. This dataset provides - United States Government Budget Value - actual values, historical data, forecast, chart, statistics, economic calendar and news.

  14. k

    World Competitiveness Ranking based on Criteria

    • datasource.kapsarc.org
    Updated Mar 13, 2024
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    (2024). World Competitiveness Ranking based on Criteria [Dataset]. https://datasource.kapsarc.org/explore/dataset/world-competitiveness-ranking-based-on-criteria-2016/
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    Dataset updated
    Mar 13, 2024
    Description

    Explore the World Competitiveness Ranking dataset for 2016, including key indicators such as GDP per capita, fixed telephone tariffs, and pension funding. Discover insights on social cohesion, scientific research, and digital transformation in various countries.

    Social cohesion, The image abroad of your country encourages business development, Scientific articles published by origin of author, International Telecommunication Union, World Telecommunication/ICT Indicators database, Data reproduced with the kind permission of ITU, National sources, Fixed telephone tariffs, GDP (PPP) per capita, Overall, Exports of goods - growth, Pension funding is adequately addressed for the future, Companies are very good at using big data and analytics to support decision-making, Gross fixed capital formation - real growth, Economic Performance, Scientific research legislation, Percentage of GDP, Health infrastructure meets the needs of society, Estimates based on preliminary data for the most recent year., Singapore: including re-exports., Value, Laws relating to scientific research do encourage innovation, % of GDP, Gross Domestic Product (GDP), Health Infrastructure, Digital transformation in companies is generally well understood, Industrial disputes, EE, Female / male ratio, State ownership of enterprises, Total expenditure on R&D (%), Score, Colombia, Estimates for the most recent year., Percentage change, based on US$ values, Number of listed domestic companies, Tax evasion is not a threat to your economy, Scientific articles, Tax evasion, % change, Use of big data and analytics, National sources, Disposable Income, Equal opportunity, Listed domestic companies, Government budget surplus/deficit (%), Pension funding, US$ per capita at purchasing power parity, Estimates; US$ per capita at purchasing power parity, Image abroad or branding, Equal opportunity legislation in your economy encourages economic development, Number, Article counts are from a selection of journals, books, and conference proceedings in S&E from Scopus. Articles are classified by their year of publication and are assigned to a region/country/economy on the basis of the institutional address(es) listed in the article. Articles are credited on a fractional-count basis. The sum of the countries/economies may not add to the world total because of rounding. Some publications have incomplete address information for coauthored publications in the Scopus database. The unassigned category count is the sum of fractional counts for publications that cannot be assigned to a country or economy. Hong Kong: research output items by the higher education institutions funded by the University Grants Committee only., State ownership of enterprises is not a threat to business activities, Protectionism does not impair the conduct of your business, Digital transformation in companies, Total final energy consumption per capita, Social cohesion is high, Rank, MTOE per capita, Percentage change, based on constant prices, US$ billions, National sources, World Trade Organization Statistics database, Rank, Score, Value, World Rankings

    Argentina, Australia, Austria, Belgium, Brazil, Bulgaria, Canada, Chile, China, Colombia, Croatia, Cyprus, Denmark, Estonia, Finland, France, Germany, Greece, Hungary, Iceland, India, Indonesia, Ireland, Israel, Italy, Japan, Jordan, Kazakhstan, Latvia, Lithuania, Luxembourg, Malaysia, Mexico, Mongolia, Netherlands, New Zealand, Norway, Oman, Peru, Philippines, Poland, Portugal, Qatar, Romania, Russia, Saudi Arabia, Singapore, Slovenia, South Africa, Spain, Sweden, Switzerland, Thailand, Turkey, Ukraine, United Kingdom, Venezuela

    Follow data.kapsarc.org for timely data to advance energy economics research.

  15. t

    Receipts of the U.S. Government

    • fiscaldata.treasury.gov
    Updated Jul 13, 2020
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    (2020). Receipts of the U.S. Government [Dataset]. https://fiscaldata.treasury.gov/datasets/monthly-treasury-statement/
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    Dataset updated
    Jul 13, 2020
    Description

    This table shows the gross receipts, refunds and net receipts for the current month, the current fiscal year-to-date and the prior fiscal year-to-date for the various receipts of the federal government. This table includes total and subtotal rows that should be excluded when aggregating data. Some rows represent elements of the dataset's hierarchy, but are not assigned values. The classification_id for each of these elements can be used as the parent_id for underlying data elements to calculate their implied values. Subtotal rows are available to access this same information.

  16. t

    Summary of Budget and Off-Budget Results and Financing of the U.S....

    • fiscaldata.treasury.gov
    Updated Jul 13, 2020
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    (2020). Summary of Budget and Off-Budget Results and Financing of the U.S. Government [Dataset]. https://fiscaldata.treasury.gov/datasets/monthly-treasury-statement/
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    Dataset updated
    Jul 13, 2020
    Description

    This summary table shows the on-budget and off-budget receipts and outlays, the on-budget and off-budget surplus/deficit, and the means of financing the budget surplus/deficit. The table also shows the budgeted amounts estimated in the President's Budget for the current fiscal year and next fiscal year for each item on the table. This table includes total and subtotal rows that should be excluded when aggregating data. Some rows represent elements of the dataset's hierarchy, but are not assigned values. The classification_id for each of these elements can be used as the parent_id for underlying data elements to calculate their implied values. Subtotal rows are available to access this same information.

  17. t

    Means of Financing the Deficit or Disposition of Surplus by the U.S....

    • fiscaldata.treasury.gov
    Updated Jul 13, 2020
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    (2020). Means of Financing the Deficit or Disposition of Surplus by the U.S. Government [Dataset]. https://fiscaldata.treasury.gov/datasets/monthly-treasury-statement/
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    Dataset updated
    Jul 13, 2020
    Description

    This table shows the net transactions for the current month, and the current and prior fiscal year-to-date, as well as account balances for the beginning of the current fiscal year and current accounting month and the close of the current accounting month. This activity is related to the means used to finance the budget deficit or to dispose of a budget surplus. An asset account would represent an asset to the United States Government, for example United States Treasury Operating Cash. A liability account would represent a liability to the United States Government, for example Borrowing from the Public. This table includes total and subtotal rows that should be excluded when aggregating data. Some rows represent elements of the dataset's hierarchy, but are not assigned values. The classification_id for each of these elements can be used as the parent_id for underlying data elements to calculate their implied values. Subtotal rows are available to access this same information.

  18. t

    Summary of Receipts, Outlays, and the Deficit/Surplus of the U.S. Government...

    • fiscaldata.treasury.gov
    Updated Jul 13, 2020
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    (2020). Summary of Receipts, Outlays, and the Deficit/Surplus of the U.S. Government [Dataset]. https://fiscaldata.treasury.gov/datasets/monthly-treasury-statement/
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    Dataset updated
    Jul 13, 2020
    Description

    This summary table shows the total amount of receipts and outlays and the amount of the budget surplus/deficit by month for the current and prior fiscal years. This table includes total and subtotal rows that should be excluded when aggregating data. Some rows represent elements of the dataset's hierarchy, but are not assigned values. The classification_id for each of these elements can be used as the parent_id for underlying data elements to calculate their implied values. Subtotal rows are available to access this same information.

  19. t

    Analysis of Change in Excess of Liabilities of the U.S. Government

    • fiscaldata.treasury.gov
    Updated Jul 13, 2020
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    (2020). Analysis of Change in Excess of Liabilities of the U.S. Government [Dataset]. https://fiscaldata.treasury.gov/datasets/monthly-treasury-statement/
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    Dataset updated
    Jul 13, 2020
    Description

    This table is a subsidiary table for Means of Financing the Deficit or Disposition of Surplus by the U.S. Government providing a detailed view of the Change in Excess of Liabilities. This table includes total and subtotal rows that should be excluded when aggregating data. Some rows represent elements of the dataset's hierarchy, but are not assigned values. The classification_id for each of these elements can be used as the parent_id for underlying data elements to calculate their implied values. Subtotal rows are available to access this same information.

  20. t

    Trust Fund Impact on Budget Results and Investment Holdings

    • fiscaldata.treasury.gov
    Updated Jul 13, 2020
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    (2020). Trust Fund Impact on Budget Results and Investment Holdings [Dataset]. https://fiscaldata.treasury.gov/datasets/monthly-treasury-statement/
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    Dataset updated
    Jul 13, 2020
    Description

    This table shows the total receipts and outlays and the resulting surplus or deficit (shown on the table as excess) for the current month and the current fiscal year-to-date for all federal trust funds. The table also shows the totals for securities held as investments by the federal trust funds for the beginning of the fiscal year and the beginning and ending of the current accounting month. A trust fund is a type of account, designated by law, for receipts or offsetting receipts dedicated to specific purposes and the expenditure of these receipts. This table includes total and subtotal rows that should be excluded when aggregating data. Some rows represent elements of the dataset's hierarchy, but are not assigned values. The classification_id for each of these elements can be used as the parent_id for underlying data elements to calculate their implied values. Subtotal rows are available to access this same information.

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Warwick J. McKibbin; Geoffrey Shuetrim (2025). Replication dataset and calculations for PIIE Briefing 25-2 The US Revenue Implications of President Trump’s 2025 Tariffs by Warwick McKibbin and Geoffrey Shuetrim (2025). [Dataset]. https://www.piie.com/publications/piie-briefings/2025/us-revenue-implications-president-trumps-2025-tariffs
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Replication dataset and calculations for PIIE Briefing 25-2 The US Revenue Implications of President Trump’s 2025 Tariffs by Warwick McKibbin and Geoffrey Shuetrim (2025).

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Dataset updated
Apr 22, 2025
Dataset provided by
Peterson Institute for International Economicshttp://www.piie.com/
Authors
Warwick J. McKibbin; Geoffrey Shuetrim
Description

This data package includes the underlying data to replicate the charts, tables, and calculations presented in The US Revenue Implications of President Trump’s 2025 Tariffs, PIIE Briefing 25-2.

If you use the data, please cite as:

McKibbin, Warwick, and Geoffrey Shuetrim. 2025. The US Revenue Implications of President Trump’s 2025 Tariffs. PIIE Briefing 25-2. Washington: Peterson Institute for International Economics.

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