In early April, claiming to boost the country's domestic economy, President Trump made an executive order to implement new, widespread tariffs. In addition to the 10 percent baseline tariff imposed on all U.S. imports, Trump also announced specific tariffs on a number of important trading partners, such as the European Union, China, and Vietnam, which account for over 40 percent of all U.S. imports. According to a survey taken just after the announcement, roughly 20 percent of surveyed Americans were planning to make purchases because they expected prices to increase as a result of the tariffs.
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.
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U.S. tariffs on imported components, such as semiconductor chips, AI processors, and cloud infrastructure, have raised production costs for personal AI assistant technology providers. Many of these components are sourced from regions like Asia, where tariff increases have resulted in higher prices for the hardware necessary for AI assistants.
As a result, U.S.-based manufacturers may pass these increased costs onto consumers, potentially slowing adoption, especially among small to medium enterprises (SMEs). The impact of tariffs is particularly significant in the chatbot and customer service application segments, where scalability and efficiency are critical. U.S. tariffs are estimated to affect 10-15% of the personal AI assistant market, with cloud-based AI assistants and natural language processing technologies being the most impacted.
The U.S. tariffs have impacted approximately 10-15% of the personal AI assistant market, particularly affecting chatbot solutions and cloud-based AI assistants that rely on imported semiconductor chips and cloud infrastructure.
In the week of May 14, 2025, roughly 44 percent of people in the United States said that they were willing to spend up to five percent more on products. This comes in the wake of trade tariffs that President Trump recently announced.
On April 9, 2025, the U.S. imposed high import tariffs on Chinese goods. Average U.S. tariffs on imports from China reached ***** percent on April 10, 2025. In comparison, import levies on exports from the rest of the world were at around **** percent. In response to increased U.S. tariffs, China imposed retaliatory levies, averaging ***** percent as of April 12, 2025. After trade talks, the U.S. and China agreed to temporarily lower mutual trade barriers, leading to average U.S. tariffs of **** percent and average Chinese tariffs of **** percent on May 14, 2025.
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US tariffs could have a substantial impact on the global contextual marketing market, especially in terms of cost structures and international trade dynamics. With contextual marketing relying heavily on digital platforms, mobile devices, and software solutions, tariffs on technology imports and services could result in higher operational costs for businesses.
For sectors such as activity-based marketing, which accounts for over 51.3% of the market, tariff-related increases could range between 2% and 4%, potentially leading to higher prices for end consumers. The mobile device sector, crucial for contextual delivery, may face a 3-5% rise in component costs.
Furthermore, industries like retail and consumer goods, which hold a 23.7% market share, could see reduced profit margins due to tariff-related cost increases. While tariffs may also drive companies to consider domestic alternatives to avoid additional charges, they may be faced with challenges in maintaining the competitive pricing needed in the fast-evolving digital marketing sector.
The US tariffs are expected to impact sectors such as activity-based marketing (2-4%) and mobile devices (3-5%) in terms of increased costs, which could affect both pricing and competitiveness. Retail & consumer goods may experience a 1-3% rise in operational expenses due to increased import costs.
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U.S. tariffs on imported target drone components, particularly from China, have increased production costs for drone manufacturers. Key components like sensors, motors, and avionics are sourced from regions affected by tariffs, leading to higher overall prices for U.S. drone manufacturers.
These increased costs could limit affordability for smaller government contractors and military clients, potentially slowing down adoption rates for advanced target drone systems. To mitigate tariff impacts, many companies are exploring alternative supply chains, increasing domestic production, or developing partnerships with non-tariffed countries.
Despite these challenges, demand for target drones, particularly in military and government sectors, remains strong. The tariff impact is particularly significant for the aerial target drones and autonomous target drones, with approximately 20-25% of the market affected by increased costs due to tariffs.
The U.S. tariffs have impacted approximately 20-25% of the target drone market, particularly in the aerial target drones and autonomous drone segments, which rely on imported components.
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The U.S. trade tariff increases imposed in April 2025 were estimated to lead to a *** percent decrease in Slovakia's gross domestic product (GDP) in 2025, while in Hungary, this figure was expected to reach *** percent.
According to estimates, President Trump's proposals to impose universal tariffs as well as tariffs on Chinese, Canadian, and Mexican imports would considerably increase the average tariff rate. If Trump's proposals go into effect, it is estimated that the average tariff rate of all imports would almost triple, marking the highest rate in the United States since 1969.
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The U.S. tariffs on electronic components, including current transducers, have affected the market by increasing the cost of production. Components such as magnetic cores, semiconductors, and other raw materials, which are often sourced from regions like China, have become more expensive due to tariffs.
As a result, U.S. manufacturers face higher costs, which may lead to increased prices for current transducers, particularly for applications in industries like motor drives and electric vehicles. To mitigate these challenges, companies are exploring alternate supply chains, increasing domestic production, or passing some costs onto consumers.
Despite the tariff impact, the demand for current transducers remains strong, driven by their growing application in motor control, energy management, and electric vehicles. The tariff impact is estimated to affect around 15-20% of the market, especially in segments that rely on imported components.
The U.S. tariffs have impacted approximately 15-20% of the current transducer market, particularly in the motor drive and open-loop current transducer segments, which rely heavily on imported components.
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The US tariffs on imported AI software and hardware components are causing significant disruptions in the AI in underwriting market. These tariffs increase the cost of cloud-based solutions and software tools used by insurers, which may slow down the adoption of AI-driven underwriting processes.
The tariffs especially affect sectors that rely heavily on machine learning and risk evaluation technologies, such as the insurance industry. These cost increases may force companies to delay AI implementations or reduce investment in the technology.
As a result, the market's growth could be affected, especially in smaller companies and startups within the underwriting space that cannot absorb these higher costs. Additionally, the disruptions in the global supply chain are further delaying the delivery of critical AI solutions.
According to a 2025 survey, over one-quarter of Americans were planning on making electronics purchases because they expect prices to increase across the country as a result of Trump's proposed tariffs on all imported goods.
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Australia Tariff Rate: Applied: Weighted Mean: All Products data was reported at 0.990 % in 2022. This records an increase from the previous number of 0.810 % for 2021. Australia Tariff Rate: Applied: Weighted Mean: All Products data is updated yearly, averaging 3.150 % from Dec 1991 (Median) to 2022, with 29 observations. The data reached an all-time high of 18.560 % in 1991 and a record low of 0.710 % in 2020. Australia 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 Australia – Table AU.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 tariff data from the United Nations Conference on Trade and Development's Trade and Development's Trade Analysis and Information System (TRAINS) database and global imports data from the United Nations Statistics Division's Comtrade database.;;The tariff data for the European Union (EU) apply to EU Member States in alignment with the EU membership for the respective countries/economies and years. In the context of the tariff data, the EU membership for a given country/economy and year is defined for the entire year during which the country/economy was a member of the EU (irrespective of the date of accession to or withdrawal from the EU within a given year). The tariff data for the EU are, thus, applicable to Belgium, France, Germany, Italy, Luxembourg, and the Netherlands (EU Member State(s) since 1958), Denmark and Ireland (EU Member State(s) since 1973), the United Kingdom (EU Member State(s) from 1973 until 2020), Greece (EU Member State(s) since 1981), Spain and Portugal (EU Member State(s) since 1986), Austria, Finland, and Sweden (EU Member State(s) since 1995), Czech Republic, Estonia, Cyprus, Latvia, Lithuania, Hungary, Malta, Poland, Slovakia, and Slovenia (EU Member State(s) since 2004), Romania and Bulgaria (EU Member State(s) since 2007), Croatia (EU Member State(s) since 2013). For more information, please revisit the technical note on bilateral applied tariff (https://wits.worldbank.org/Bilateral-Tariff-Technical-Note.html).
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US tariffs on reinsurance-related services, particularly those affecting global reinsurers, could increase operational costs for companies relying on international markets for risk mitigation. Tariffs could raise the cost of certain reinsurance services and contracts by 5-10%, particularly for those involving cross-border transactions.
The cost of services for property and casualty reinsurance may increase as reinsurers face higher premiums for cross-border agreements. This could lead to higher costs for insurance providers and, in turn, increase premiums for end consumers. Additionally, higher tariffs may disrupt the flow of capital and data between reinsurers and brokers, further complicating the market landscape.
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Luxembourg LU: Tariff Rate: Most Favored Nation: Weighted Mean: Primary Products data was reported at 3.180 % in 2016. This records an increase from the previous number of 2.520 % for 2015. Luxembourg LU: Tariff Rate: Most Favored Nation: Weighted Mean: Primary Products data is updated yearly, averaging 3.550 % from Dec 1988 (Median) to 2016, with 29 observations. The data reached an all-time high of 9.960 % in 1995 and a record low of 2.070 % in 2012. Luxembourg LU: Tariff Rate: Most Favored Nation: Weighted Mean: Primary Products data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Luxembourg – Table LU.World Bank.WDI: Trade Tariffs. Weighted mean most favored nations tariff is the average of most favored nation 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. Import weights were calculated using the United Nations Statistics Division's Commodity Trade (Comtrade) database. Primary products are commodities classified in SITC revision 3 sections 0-4 plus division 68 (nonferrous metals).; ; 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.; ;
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Finland FI: Tariff Rate: Applied: Weighted Mean: All Products data was reported at 1.960 % in 2016. This records an increase from the previous number of 1.890 % for 2015. Finland FI: Tariff Rate: Applied: Weighted Mean: All Products data is updated yearly, averaging 2.270 % from Dec 1988 (Median) to 2016, with 29 observations. The data reached an all-time high of 6.280 % in 1995 and a record low of 1.310 % in 2012. Finland FI: 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 Finland – Table FI.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.; ;
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Tariff rate, most favored nation, simple mean, all products (%) in Vietnam was reported at 9.65 % in 2022, according to the World Bank collection of development indicators, compiled from officially recognized sources. Vietnam - Tariff rate, most favored nation, simple mean, all products - actual values, historical data, forecasts and projections were sourced from the World Bank on June of 2025.
This dataset is restricted, for more information please contact the author. Data were collected from multiple sources:The Electricity & Co-Generation Regulatory AuthoritySaudi Electricity companyWeb news article (2015, December 28). Increase of Fuel, Electricity and Water prices. Retrieved from https://akhbaar24.argaam.com/article/detail/255091accessed on March 22, 2018.In October 1984, the government adopted a Tariff that increased with increasing consumption. The changes of Tariffs started in November 1984.Tariff approved by Council of Ministries 170 and become effective in October 2000. This Tariff remained effective for approximately ten years The residential, agricultural, mosques, and charitable societies remained unchanged till 2018In 2010, a new tariff for government, commercial, and industrial consumption came into force, this was adopted by a decision of ECRA's board, to set tariffs for non-residential consumption with an upper limit of SR0.26/kWh.In 2015, the total value of electricity consumed by the residential sector was worth about 38 billion U.S. dollars.In 2018, the Council of Ministers has approved gradual revision of energy prices in the Kingdom including changes to electricity tariffs effective from Jan. 1. 2018, the Electricity and Cogeneration Regulatory Authority (ECRA) announced that new prices will take effect on January 1st, 2018.source: ECRACitation: Alghamdi, Abeer. 2018. “Changes in Saudi Arabia Electricity Prices.” [dataset]. https://datasource.kapsarc.org/explore/dataset/electricity-prices-in-saudi-arabia/information/.
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US tariffs could have a considerable impact on the robotic sensors market, particularly on imported components such as position sensors and other critical sensor technologies used in manufacturing robotics.
The imposition of tariffs on key components like semiconductors, sensors, and electrical parts could lead to a 4-6% increase in production costs, making robotic sensors more expensive. This price increase could deter some manufacturers from adopting advanced robotic technologies, particularly in cost-sensitive industries.
Additionally, the disruption in supply chains due to tariffs could lead to delays in sensor availability, affecting robotic production timelines. The manufacturing sector, which accounts for over 40% of the market share, could be the most affected due to its heavy reliance on imported sensor components.
While larger companies might absorb the cost increase, smaller businesses could face difficulties in maintaining competitive pricing. However, despite these challenges, the long-term growth potential of the robotic sensors market remains positive due to the growing demand for automation.
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The position sensor segment, which holds 18.5% of the market share, could see a 4-6% increase in production costs due to tariffs on imported sensor components and semiconductor materials.
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Belarus BY: Tariff Rate: Applied: Weighted Mean: All Products data was reported at 2.270 % in 2021. This records an increase from the previous number of 1.760 % for 2020. Belarus BY: Tariff Rate: Applied: Weighted Mean: All Products data is updated yearly, averaging 2.630 % from Dec 1996 (Median) to 2021, with 19 observations. The data reached an all-time high of 9.500 % in 1997 and a record low of 1.510 % in 2017. Belarus BY: 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 Belarus – Table BY.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 tariff data from the United Nations Conference on Trade and Development's Trade and Development's Trade Analysis and Information System (TRAINS) database and global imports data from the United Nations Statistics Division's Comtrade database.;;The tariff data for the European Union (EU) apply to EU Member States in alignment with the EU membership for the respective countries/economies and years. In the context of the tariff data, the EU membership for a given country/economy and year is defined for the entire year during which the country/economy was a member of the EU (irrespective of the date of accession to or withdrawal from the EU within a given year). The tariff data for the EU are, thus, applicable to Belgium, France, Germany, Italy, Luxembourg, and the Netherlands (EU Member State(s) since 1958), Denmark and Ireland (EU Member State(s) since 1973), the United Kingdom (EU Member State(s) from 1973 until 2020), Greece (EU Member State(s) since 1981), Spain and Portugal (EU Member State(s) since 1986), Austria, Finland, and Sweden (EU Member State(s) since 1995), Czech Republic, Estonia, Cyprus, Latvia, Lithuania, Hungary, Malta, Poland, Slovakia, and Slovenia (EU Member State(s) since 2004), Romania and Bulgaria (EU Member State(s) since 2007), Croatia (EU Member State(s) since 2013). For more information, please revisit the technical note on bilateral applied tariff (https://wits.worldbank.org/Bilateral-Tariff-Technical-Note.html).
In early April, claiming to boost the country's domestic economy, President Trump made an executive order to implement new, widespread tariffs. In addition to the 10 percent baseline tariff imposed on all U.S. imports, Trump also announced specific tariffs on a number of important trading partners, such as the European Union, China, and Vietnam, which account for over 40 percent of all U.S. imports. According to a survey taken just after the announcement, roughly 20 percent of surveyed Americans were planning to make purchases because they expected prices to increase as a result of the tariffs.