In 2025, President Trump announced plans to implement a universal baseline tariff of 10 percent. Estimates show that a 10 percent universal tariff on imported goods would raise U.S. revenue by 2.95 trillion U.S. dollars, while a 20 percent tariff would raise revenue by 2.62 trillion U.S. dollars. Comparatively, imports before Trump's proposed taxes would increase revenue by 3.28 trillion U.S. dollars. By enacting tariffs on all imports, significantly less foreign-produced goods would be purchased, thus decreasing the overall amount of imported goods.

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.

Graph and download economic data for Federal government current tax receipts: Taxes on production and imports (NA000324Q) from Q1 1947 to Q1 2025 about receipts, imports, tax, federal, production, government, GDP, and USA.

Customs and other import duties (% of tax revenue) in United States was reported at 2.7662 % in 2023, according to the World Bank collection of development indicators, compiled from officially recognized sources. United States - Customs and other import duties (% of tax revenue) - actual values, historical data, forecasts and projections were sourced from the World Bank on June of 2025.

In the United States, the revenue from customs duty amounted to 80 billion U.S. dollars in 2023. The forecast predicts a slight increase in customs duty revenue to 97 billion U.S. dollars in 2024, and an increase over the next decade to 96 billion U.S. dollars by 2034.

China Government Revenue: Tax: Year to Date: Tariffs data was reported at 48.300 RMB bn in Mar 2025. This records an increase from the previous number of 31.600 RMB bn for Feb 2025. China Government Revenue: Tax: Year to Date: Tariffs data is updated monthly, averaging 128.732 RMB bn from Jan 2007 (Median) to Mar 2025, with 211 observations. The data reached an all-time high of 299.785 RMB bn in Dec 2017 and a record low of 12.274 RMB bn in Jan 2007. China Government Revenue: Tax: Year to Date: Tariffs data remains active status in CEIC and is reported by Ministry of Finance. The data is categorized under China Premium Database’s Government and Public Finance – Table CN.FA: Government Revenue: Tax.

The dataset comprises three schedules categorising each of the HS 2017 6-digit product codes as A: nonsensitive, B: sensitive or C: excluded. The "offer" schedule is derived from the officially published offers where "none" indicates missing categorisations. The "repaired offer" amends the "offer" by categorising the missing codes such that the tariff revenue raised is maximised. The "maximum" schedule is constructed from scratch by categorising all codes such that the tariff revenue raised is maximised.

For details, please refer to the associated publications.

Russia Federal Government Revenue: Oil & Gas: Export Tariffs data was reported at 47.300 RUB bn in Mar 2025. This records a decrease from the previous number of 69.100 RUB bn for Feb 2025. Russia Federal Government Revenue: Oil & Gas: Export Tariffs data is updated monthly, averaging 132.400 RUB bn from Jan 2018 (Median) to Mar 2025, with 87 observations. The data reached an all-time high of 348.200 RUB bn in Apr 2022 and a record low of -69.000 RUB bn in Jul 2024. Russia Federal Government Revenue: Oil & Gas: Export Tariffs data remains active status in CEIC and is reported by Ministry of Finance of the Russian Federation. The data is categorized under Russia Premium Database’s Government and Public Finance – Table RU.FB006: Federal Government Revenue and Expenditure: General.

Graph and download economic data for Federal government current tax receipts: Taxes on production and imports: Customs duties (B235RC1A027NBEA) from 1929 to 2024 about receipts, imports, tax, federal, production, government, GDP, and USA.

During 2024, the annual import tax revenue of the Mexican Federal Government was around 137.82 billion Mexican pesos, that represents around a 37 percent increased when compared to the previous year. Nonetheless, the Mexican Government expects this figure to increase even further by adding new tariffs to foreign e-commerce platforms. Specifically, platforms from countries without a free trade agreement, such as Temu or Shein, will start paying a 19 percent tariff (depending on specific circumstances). This new import tax has two main objectives, protecting the national industries like manufacturing and increasing Government revenue.

China Government Budgetary Revenue: Central: Tax: Tariffs data was reported at 247,500.000 RMB mn in 2025. This records a decrease from the previous number of 269,000.000 RMB mn for 2024. China Government Budgetary Revenue: Central: Tax: Tariffs data is updated yearly, averaging 255,250.000 RMB mn from Dec 2000 (Median) to 2025, with 26 observations. The data reached an all-time high of 314,000.000 RMB mn in 2018 and a record low of 57,100.000 RMB mn in 2000. China Government Budgetary Revenue: Central: Tax: Tariffs data remains active status in CEIC and is reported by Ministry of Finance. The data is categorized under China Premium Database’s Government and Public Finance – Table CN.FAS: Budget: General Public Budget Revenue & Expenditure: Central.

As of April 9, 2025, the United States levied a revised baseline of 10 percent on all goods imported from countries of the Middle East and North Africa .Based on the initial tariff calculation of April 3, the rates of imported goods would have varied by country in the region, with Syria and Iraq at 41 and 39 percent, respectively. Tariffs and their effects he intertwined nature of global trade and supply chains implies that the shockwaves of significant policy changes and economic turbulences spread more easily across countries. This was illustrated in the effects of new United States tariffs on Arab countries, where projections show a 1.4 percent decrease in investments in the Gulf Cooperation Council (GCC). Meanwhile, the impact of these tariffs on the Middle East and North Africa (MENA) imports forecast a 28 percent decrease in imports from the United States to the Arab region. Middle East-United States trade relations The nature of trade relationships between the United States and the Middle East is often influenced by geopolitical and security realities, with Israel, UAE, and Saudi Arabia being the leading bilateral trading partners. A particularly strong trade relationship exists between the GCC countries and the United States, evident in the value of exports from the former to the latter. On the other hand, the value of exports from the broader Arab region to the United States fell considerably in the last decade, largely due to petroleum and oil revenue decrease.

Governments use tariffs to manage the politics of international economic integration. To navigate competing demands on trade policy, governments can target tariff rates to individual products. But existing theories miss an important aspect of tariffs: they also need to be enforced at border crossings, which for some governments creates substantial challenges. Faced with high tariffs, firms can misclassify their products into categories with lower tariff rates. Pointing to the potential for such tariff evasion, I discuss the difficulties for governments in targeting tariffs for political gain, and I derive implications for trade politics. Constraints on the ability of governments to enforce tariffs, in the form of low bureaucratic capacity, emerge as an institutional determinant of trade policy, discouraging the use of product-specific tariff rates. Disaggregated tariff data provide empirical evidence for this argument. The article identifies an institutional constraint on trade politics, contributes to growing literatures on firm heterogeneity and on illicit cross-border economic activity, and speaks to debates on trade policy and government revenue.

Ericsson's ADRs dropped 11% due to a profit miss and tariff worries, despite North American growth. Earnings fell short of expectations, raising concerns for the telecommunications industry.

Tonga's Tariffs and other import duties (% of revenue) is 9.4% which is the 41st highest in the world ranking. Transition graphs on Tariffs and other import duties (% of revenue) in Tonga and comparison bar charts (USA vs. China vs. Japan vs. Tonga), (Saint Vincent vs. the Grenadines vs. Seychelles vs. Tonga) are used for easy understanding. Various data can be downloaded and output in csv format for use in EXCEL free of charge.

tariff rates for 2017 was 3.13%, a 0.23% increase from 2016.

<ul style='margin-top:20px;'>

<li> tariff rates for 2016 was <strong>2.90%</strong>, a <strong>0.04% decline</strong> from 2015.</li>
<li> tariff rates for 2015 was <strong>2.94%</strong>, a <strong>1.51% decline</strong> from 2014.</li>
<li> tariff rates for 2014 was <strong>4.45%</strong>, a <strong>0.1% increase</strong> from 2013.</li>
</ul>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.

If proposed tariffs of 25 percent on goods imported into the United States from Mexico and Canada were put into effect, tax revenue would be impacted. Tax revenue from Mexican wine imports are projected to increase by 108 million U.S. dollars while taxes from Mexican spirits imports would decrease by 1.4 billion dollars.

China Govt Revenue: Tax: Tariffs data was reported at 284,800.000 RMB mn in 2018. This records a decrease from the previous number of 299,785.000 RMB mn for 2017. China Govt Revenue: Tax: Tariffs data is updated yearly, averaging 10,307.000 RMB mn from Dec 1950 (Median) to 2018, with 69 observations. The data reached an all-time high of 299,785.000 RMB mn in 2017 and a record low of 356.000 RMB mn in 1950. China Govt Revenue: Tax: Tariffs data remains active status in CEIC and is reported by Ministry of Finance. The data is categorized under Global Database’s China – Table CN.FA: Government Revenue: Tax.

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...

The Household Impacts of Tariffs (HIT) simulation tool enables users to simulate how changes in import tariffs impact the incomes of households across the income distribution. The website provides estimates of (i) price changes induced by tariff reforms, and (ii) the resulting impact on the real income of households in different percentiles of the income distribution via their impact on (iii) the cost of consumption and (iv) their incomes using detailed data on households’ income and consumption portfolios derived from representative household surveys harmonized with tariff data.