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.

United States US: Tariff Rate: Applied: Weighted Mean: All Products data was reported at 1.670 % in 2016. This records a decrease from the previous number of 1.690 % for 2015. United States US: Tariff Rate: Applied: Weighted Mean: All Products data is updated yearly, averaging 1.960 % from Dec 1989 (Median) to 2016, with 27 observations. The data reached an all-time high of 3.950 % in 1992 and a record low of 1.540 % in 2007. United States US: Tariff Rate: Applied: Weighted Mean: All Products data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s United States – Table US.World Bank.WDI: Trade Tariffs. Weighted mean applied tariff is the average of effectively applied rates weighted by the product import shares corresponding to each partner country. Data are classified using the Harmonized System of trade at the six- or eight-digit level. Tariff line data were matched to Standard International Trade Classification (SITC) revision 3 codes to define commodity groups and import weights. To the extent possible, specific rates have been converted to their ad valorem equivalent rates and have been included in the calculation of weighted mean tariffs. Import weights were calculated using the United Nations Statistics Division's Commodity Trade (Comtrade) database. Effectively applied tariff rates at the six- and eight-digit product level are averaged for products in each commodity group. When the effectively applied rate is unavailable, the most favored nation rate is used instead.; ; World Bank staff estimates using the World Integrated Trade Solution system, based on data from United Nations Conference on Trade and Development's Trade Analysis and Information System (TRAINS) database and the World Trade Organization’s (WTO) Integrated Data Base (IDB) and Consolidated Tariff Schedules (CTS) database.; ;

This dataset shows active grain (corn, soybeans, wheat, and sorghum) rail tariff rates to the Mexico border for a number of U.S. locations, border crossings, car types, and shipment sizes for BNSF, Union Pacific, and Kansas City Southern (KCS). These rates are Rule 11 rates, where a through rate from a U.S. origin to a Mexico destination is divided into a rate from a U.S. origin to the border and a rate from the border to a Mexico destination. The U.S. railroads began reporting only Rule 11 rates to the border in January 2022 following the implementation of a VAT tax on the Mexican portion of the rail shipment. This dataset only contains rates on the U.S. to-the-border portion of the shipment.

The rates are collected from the BNSF, UP, and KCS websites. The railroads do not update the tariffs on defined interval, but do typically have at least one update a year before that commodity's harvest season. The tariff rates are joined to fuel surcharges that are updated monthly. A row in the dataset represents the active tariff rate for that shipment type (route, size, etc.) and the fuel surcharge for that railroad in a particular month. In the case where a tariff rate is changed mid-month, the row is an average of any rates that were active during that month.

Fuel surcharges are published by the railroads on a monthly, per-mile basis and are collected separately from the tariff documents (See USDA's fuel surcharge data at https://agtransport.usda.gov/d/f883-g4tq). To compute a per car fuel surcharge, the U.S. origin to the border rail route distance is approximated using the Department of Transportation's National Rail Network Lines (NARL) dataset and a shortest-path computation.

KCS is now CPKC, but KCS rates are still reported separately at https://web.kcsouthern.com/AgricultureTariff/Default.aspx.

The dataset is intended to capture most of the published tariffs for corn, soybean, and wheat shipments to Mexico. However, some routes and tariff updates may not be included.

Residential electricity prices data for Saudi Arabia, UAE, Bahrain, Oman and Kuwait collected from multiple sources. Saudi Arabia electricity tariffs: KAPSARC dataOman: Authority for Electricity Regulations - Link 2019 Annual Report Bahrain: Electricity & Water Authority - Link - ​​​​​​​​​​​​​​​​​​​​​Electricity Consumption Tariff for the years 2016-2019UAE electricity prices: Dubai: Dubai Electricity & Water Authority - Link Sharjah: Sharjah Electricity & Water Authority - Link Access Abu Dhabi prices dataset Link, Source: Abu Dhabi Distribution Company - Link Water & Electricity Tariffs 2017Other emirates in UAE: Federal Electricity & Water Authority - Link Global average price - link World average price is 0.14 U.S. Dollar per kWh for household users and 0.13 U.S. Dollar per kWh for business users.Note: Global average price for world countries include all items in the electricity bill such as the distribution and energy cost, various environmental and fuel cost charges and taxes.All prices are converted to (US cent/KWh). Citation: Alghamdi, Abeer. 2020. “GCC Residential Electricity Tariffs.” [dataset]. https://datasource.kapsarc.org/explore/dataset/gcc-electricity/information/?disjunctive.country_city&disjunctive.category&disjunctive.slabs.

This data set contains rail tariff rates for DDGS by railroad, and train type, for select origin/destination pairs. These data are collected monthly from individual railroad websites.

This data set contains rail tariff rates by railroad, commodity (corn, soybeans, and wheat), and train type, for select origin/destination pairs. These data are collected monthly from individual railroad websites.

Techsalerator’s Import/Export Trade Data for China

Techsalerator’s Import/Export Trade Data for China provides an extensive and detailed collection of information on international trade activities involving Chinese companies. This dataset offers a thorough analysis of trade transactions, documenting and categorizing imports and exports across various industries within China.

To obtain Techsalerator’s Import/Export Trade Data for China, please contact info@techsalerator.com or visit https://www.techsalerator.com/contact-us with your specific requirements. Techsalerator will provide a customized quote based on your data needs, with delivery available within 24 hours. Ongoing access options can also be discussed.

Techsalerator's Import/Export Trade Data for China delivers an in-depth examination of trade activities, integrating data from customs reports, trade agreements, and shipping records. This comprehensive dataset assists businesses, investors, and trade analysts in understanding China’s trade landscape in detail.

Key Data Fields

• Company Name: Lists the companies involved in trade transactions, helping identify potential partners or competitors and track industry-specific trade patterns.
• Trade Volume: Details the quantity or value of goods traded, offering insights into the scale and economic impact of trade activities.
• Product Category: Specifies the types of goods traded, such as electronics or textiles, aiding in understanding market demand and supply chain dynamics.
• Import/Export Country: Identifies the countries of origin or destination for traded goods, providing insights into global trade relationships and market access.
• Transaction Date: Records the date of transactions, revealing seasonal trends and shifts in trade dynamics over time.

Top Trade Trends in China

• Trade Balance Dynamics: China’s trade balance exhibits significant fluctuations, influenced by major partners such as the United States and the European Union. Trade policies and negotiations play a crucial role in addressing imbalances and shaping trade relationships.
• US-China Trade Relations: The trade relationship with the United States remains pivotal, influenced by agreements and tariffs. This partnership impacts various aspects of China’s trade policies and practices.
• Expansion of Global Trade Networks: China is increasingly broadening its trade partners and markets, reflecting a trend towards more extensive global trade engagement.
• Growth in Technological Exports: China continues to experience substantial trade in technology products, including electronics and machinery, which are key components of its export economy.
• Emphasis on Sustainable Trade Practices: There is a growing focus on integrating sustainability into trade policies, promoting environmentally friendly practices and technologies.

Notable Companies in Chinese Trade Data

• Huawei Technologies: A leading telecommunications company involved in exporting and importing advanced technology and electronics, playing a significant role in China’s trade dynamics.
• Lenovo: A major player in the technology sector, known for its global trade in computing products and electronics.
• China National Petroleum Corporation (CNPC): A key entity in the energy sector, involved in the import and export of oil and gas products.
• Alibaba Group: A major e-commerce company that facilitates a substantial volume of international trade through its platforms.
• BYD: A significant player in the electric vehicle and battery industry, impacting China’s trade in automotive technology and related components.

Accessing Techsalerator’s Data

To obtain Techsalerator’s Import/Export Trade Data for China, please contact us at info@techsalerator.com with your requirements. We will provide a customized quote based on the number of data fields and records needed, with delivery available within 24 hours. Ongoing access options can also be discussed.

Included Data Fields:

• Company Name
• Trade Volume
• Product Category
• Import/Export Country
• Transaction Date
• Shipping Details
• Customs Codes
• Trade Value

For detailed insights into China’s import and export activities and trends, Techsalerator’s dataset is an invaluable resource for staying informed and making strategic decisions.

This dataset contains historical monthly (from June 2010 to April 2025) rail tariff rates by railroad, commodity (corn, soybeans, and wheat), and train type, for select origin/destination pairs.

Beginning May 2025, upgraded monthly tariff data are published here: https://agtransport.usda.gov/d/3az4-jkr6. The upgrade almost doubles the number of published rates, from 38 origin-destination-railroad combinations to 70. Most of the new data go back to at least January 2022.

This data set contains rail tariff rates for ethanol by railroad, and train type, for select origin/destination pairs. These data are collected monthly from individual railroad websites.

This table represents the breakdown of taxes that are received by the federal government. Federal taxes received are represented as deposits in the Deposits and Withdrawals of Operating Cash table. All figures are rounded to the nearest million.

This table represents the breakdown of tax refunds by recipient (individual vs business) and type (check vs electronic funds transfer). Tax refunds are also represented as withdrawals in the Deposits and Withdrawals of Operating Cash table. All figures are rounded to the nearest million. As of February 14, 2023, Table VI Income Tax Refunds Issued was renamed to Table V Income Tax Refunds Issued within the published report.

This table represents the issues and redemption of marketable and nonmarketable securities. All figures are rounded to the nearest million.

This table represents the breakdown of total public debt outstanding as it relates to the statutory debt limit. All figures are rounded to the nearest million.

Get data on the daily cash and debt operations of the U.S. Treasury, including cash balance, deposits, and withdrawals; income tax refunds; and debt transactions.

This table represents deposits and withdrawals from the Treasury General Account. A summary of changes to the Treasury General Account can be found in the Operating Cash Balance table. All figures are rounded to the nearest million.

This table represents the amount Treasury has in short-term cash investments. Deposits and withdrawals of short-term cash investments are also represented in the Deposits and Withdrawals of Operating Cash table. This program was suspended indefinitely in 2008. All figures are rounded to the nearest million. As of February 14, 2023, Table V Short Term Cash Investments will no longer be updated and removed from the published report. The historical data will remain available.

This table represents cash basis adjustments to the issues and redemptions of Treasury securities in the Public Debt Transactions table. All figures are rounded to the nearest million.