This statistic shows the results of a survey conducted among American companies in China on the perceived impact on their businesses of the U.S.-China trade tariffs as of September 2018. During the survey period, **** percent of the surveyed American companies in China responded that the second round of 60 billion U.S. dollars tariffs imposed by China on the U.S. imports had a strong negative impact on their business.

According to a 2024 survey, roughly one-third of respondents who identified as Republicans favored higher tariffs on U.S. trade partners. In comparison, a similar share of Democrats favored lower tariffs.

This poll is part of a continuing series of monthly surveys that solicit public opinion on the presidency and on a range of other political and social issues. Respondents' opinions of President Bill Clinton, Bob Dole, and Newt Gingrich were elicited, along with assessments of Clinton's handling of his job as president, foreign policy, the economy, the situation in Bosnia, and United States trade relationships with Japan. The role of the United Nations was examined in detail, with specific questions on the situation in Bosnia. Other topics included commercial airline safety, tariffs, the criminal justice system, the O.J. Simpson trials, and the quality of American versus Japanese automobiles. Background information on respondents includes voter registration status, political party, political orientation, education, age, sex, race, and family income.

According to a 2024 survey, roughly two-thirds of Americans thought that increasing tariffs on foreign goods would increase prices in the country. Another ten percent agreed that increasing tariffs would have no great effect on prices in the U.S.

Public opinion poll on: Congress; Economics; Elections; Ideology; Information; Middle East; Mood; Notable People; Political Partisanship; Presidency; Presidential Approval; Problems; Ratings; Religion; Terrorism; Values; Veterans; Vote for President; War.

Passing on the increased costs was the leading measure businesses in Japan decided on in response to the Trump administration's tariffs. In a survey conducted in April 2025, only **** percent of respondents stated that the tariff policy would impel their businesses to shift production to the United States.

Public opinion poll on: Animals; Asia; Business; China; Communications Technology; Congress; Consumer; Economics; Elections; Energy; Environment; Europe; Family; Finances; Foreign Policy; Future; Government; Groups and Organizations; Health; Ideology; India; Information; Japan; Latin America; Local; Media; Mood; Notable People; Nuclear; Participation; Political Partisanship; Presidency; Regulation; Religion; Science; Social Media; Spending; States; Taxing; Technology; Television; Transportation.

Businesses in Japan sought various forms of support to deal with the Trump administration's tariffs, according to a survey conducted in April 2025. Almost ** percent of respondents stated that they desired updates for the latest information on tariff measures, while *************** sought governmental financing and fundraising.

Name: Measuring the flexibility achieved by a change of tariff. Summary: This dataset contains the results of a survey carried out by the Spanish electricity retailer GoiEner to assess the impact that a change of from a "flat rate" tariff towards a "time of use" tariff have. Two files are provided: The results of the survey merged with a summary of the energy consumption of the clients before and after the change of tariff. The questions of the survey. License: CC-BY-SA Acknowledge: These data have been collected in the framework of the WHY project. This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 891943. Disclaimer: The sole responsibility for the content of this publication lies with the authors. It does not necessarily reflect the opinion of the Executive Agency for Small and Medium-sized Enterprises (EASME) or the European Commission (EC). EASME or the EC are not responsible for any use that may be made of the information contained therein. Collection Date: Publication Date: December 1, 2022. DOI: 10.5281/zenodo.7382924 Other repositories: None. Author: GoiEner, University of Deusto. Objective of collection: The objective of the data collected is to assess the impact that the change of tariff has on the clients of GoiEner. In particular, the following questions wanted to be answered: How much energy conservation can trigger a change of tariff? How much time flexibility could be trigger with a Time of Use Tariff? What are the main barriers to change the behavoiur? Are there any differences on behaviour depending on the socio-cultural-psycological profile of the consumers? Description: The meaning of each column is described next: Qx_y: Answers to the survey. See the survey file attached (in Spanish) for details. X.z: Answers to question "¿En qué rango de horas se realizan las siguientes acciones en el domicilio?". Sorted from left to right, top to bottom. Idioma: Languaje used to answer the survey. Desea.dar.su.CU: data used to de-anonymize the answers. {P,F,V}{19,20,21}: total energy consumed during the peak, flat and valley period of the day between 6/19 to 5/20 (19), 6/20 to 5/21 (20) and 6/21 to 5/22 (21). T{19,20,21}: total energy consumed between 6/19 to 5/20 (19), 6/20 to 5/21 (20) and 6/21 to 5/22 (21). kpi2_abs: T20 - T21 kpi2_rel: kpi2_abs / T20 kpi1_{P,F,V}{19,20,21}: {P,F,V}{19,20,21} / T{19,20,21} kpi1_{P,F,V}diff: kpi1_{P,F,V}19 - kpi1_{P,F,V}21 T20DHS{19,20,21}: Cost of the energy of during the different periods using the last tariff. T20TD{19,20,21}: Cost of the energy of during the different periods using the new tariff. POWER_TARGET: Energy powerty rist indicator (https://powerpoor.eu/sites/default/files/2022-09/POWERPOOR%20D2.2%20POWER%20TARGET%20v1.0.pdf) TotalEnergyBudget: Self assessment of the energy budget of the house in Euros. Invoices20{20,21,22}: Amount of all the invoices for the house during the different periods. min30{in,pre,pst}: Cluster assigned depending on its electric behaviour pre-COVID, during the COVID lockdowns and post COVID lockdowns. See 10.5281/zenodo.7382818 for details. 5 star: ⭐⭐⭐ Preprocessing steps: Data integration (from different sources from GoiEner services); data transformation (anonymization, unit conversion, metadata generation). Reuse: This dataset is related to datasets: "A database of features extracted from different electricity load profiles datasets" (DOI 10.5281/zenodo.7382818), where time series feature extraction has been performed. Update policy: There might be a single update in mid-2023 with a repetition of the survey as there have been another change of tariff in Spain. Ethics and legal aspects: The data provided by GoiEner contained values of the CUPS (Meter Point Administration Number), which are personal data. A pre-processing step has been carried out to replace the CUPS by random 64-character hashes. Technical aspects: the survey is provided as a PDF file and the data as a CSV file compressed with zstandard. Other: None.

This paper characterizes the trade-off between the income gains and the inequality costs of trade using survey data for 54 developing countries. Tariff data on agricultural and manufacturing goods are combined with household survey data on detailed income and expenditure patterns to estimate the first-order effects of the elimination of import tariffs on household welfare. The paper assesses how these welfare effects vary across the distribution by estimating impacts on the consumption of traded goods, wage income, farm and non-farm family enterprise income, and government transfers. For each country, the income gains and the inequality costs of trade liberalization are quantified and the trade-offs between them are assessed using an Atkinson social welfare index. The analysis finds average income gains from import tariff liberalization in 45 countries and average income losses in nine countries. Across countries in the sample, the gains from trade are 1.9 percent of real household expenditure on average. We find overwhelming evidence of a trade-off between the income gains (losses) and the inequality costs (gains), which arise because trade tends to exacerbate income inequality: 45 countries face a trade-off, while only nine do not. The income gains typically more than offset the increase in inequality. In the majority of developing countries, the prevailing tariff structure thus induces sizable welfare losses

Abstract

The Ghana Millennium Development Authority's (MiDA) Agriculture Project within the Government of Ghana's Compact with the Millennium Challenge Corporation is design to improve farming in a number of areas. Under the Agricultural Project being implemented by (MiDA) some feeder roads are to be rehabilitated or reconstructed to promote development in the sector. In the first phase, about 336 km of feeder roads in eight (8) districts in two intervention zones are to be rehabilitated to reduce transportation costs and time, and increase access to major domestic and international markets. The feeder roads activity will also facilitate transportation linkages from rural areas to social service networks (including hospitals, clinics and schools).

The purpose of this project is to conduct an impact evaluation of the MiDA's Feeder Roads Activity. As stated in the Terms of Reference of the request for proposals, "the primary data for the impact evaluation will be a series of surveys similar in scope to the Consumer Price Index (CPI) survey, examining changes in prices over time Findings from the market surveys will contribute to the overall impact evaluation conducted by the Institute of Statistical, Social and Economic Research (ISSER). The Ghana Living Standards Survey (GLSS) 5+ is the primary instrument used in the overall evaluation, and 'Difference in Difference' is the proposed method of evaluation of data."

Thus, this study focuses on how prices of goods sold at local markets (that are transported on improved roads) change over time. It is also to document the changes in goods transport tariffs and passenger fares to market places served by the feeder roads.

The sample design uses a carefully tailored algorithm employed to match 154 localities that will benefit from the road improvements with an identical number of control localities that are comparatively far from the improvements. The sample size is sufficient to provide robust estimates of price effects associated with the road improvements. The minimum population for a locality to be included in the sample is 1,000, a condition imposed to help ensure that most designated items could be found in most localities.

Beginning in August 2009 interviewers visited the sample localities to obtain three price observations for each item in the defined "basket" of goods and transportation services. The final "basket" contains 39 fresh food items, 24 packaged food items, 19 non food items and 6 transportation tariffs-3 for the locality's residents' most frequent passenger destinations and 3 for the most frequent freight destinations.

Geographic coverage

308 localities in Ghana - 154 localities that will benefit from the road improvements with an identical number of control localities that are comparatively far from the improvements.

Analysis unit

The main unit of analysis is a market. Within each market, we priced the following items at up to three different vendors: 39 fresh food items, 24 packaged food items, 19 non food items and 6 transportation tariffs-3 for the locality's residents' most frequent passenger destinations and 3 for the most frequent freight destinations.

Universe

The data is only meant to represent the 308 localities surveyed. The results cannot be generalized to a larger population. The objective was not to produce estimates of national means and totals, but to estimate the parameters of an analytical model of program impact.

Kind of data

Sample survey data [ssd]

Sampling procedure

In the present application, the approach that is being used, in lieu of randomization, to select a control sample is statistical matching. A matched-pairs design was used, matching 174 (154 plus 20 replacements) treatment localities to 174 control localities using nearest-neighbor matching. Sampling was restricted, as mentioned earlier, to localities having population 1,000 or more (according to the 2000 Census) and to the 20 largest localities in each district.

The treatment population included all localities within 120 minutes estimated travel time of the nearest MiDA program road, and the control population included all localities located more than 120 minutes estimated travel time from the nearest MiDA program road. (The estimated travel times were calculated using a GIS model of the Ghana road network (documented separately).) This resulted in resulted in population sizes of 675 treatment units and 848 control units. Sampling was restricted to all of the country except Western Region.

Matching was based on a number of variables, including population, travel time to Accra, travel time to the nearest MiDA feeder road, and physiographic data.

The sample localities occur at all distances from the program roads, since it was desired to have substantial variation in the travel time to the program roads.

Because of the sample design process, the sample has reasonable spread, balance and orthogonality for a large number of design variables. Also, the sample includes a control sample for which the units are individually matched to units in the treatment sample. The sample will be a very good one for use in estimating an analytical model showing the relationship of program impact (price changes) to the Ghana MiDA feeder-road improvements, and for estimating a double-difference estimate of program impact.

Sampling deviation

Of the 308 sampled localities only one locality was removed from the sample because we were unable to locate it. This locality, Choo #0155, was not located and was removed along with its matching pair, Sabiye #0159. These localities were replaced with Suame #0812 and Ogbodzo #1264. All other localities were located and surveyed.

Mode of data collection

Face-to-face [f2f]

Research instrument

During the initial visit the NORC FM identified a subset of items on the GLSS surveys to identify and price in the market. This initial pricing and observation allowed for a detailed understanding of the impediments interviewers may encounter during data collection. After observing local conditions the NORC FM met with his counterparts on the local subcontractor team (Pentax Management and Consulting) to carry out an item by item review of the GLSS survey. Through this review NORC and Pentax were able to refine the GLSS survey to meet the needs of the current study. Standard weights and product types were identified for the majority of products, non important items were deleted in order to reduce the time of the survey, and possible fielding issues were discussed with resolutions identified.

The three questionnaires are attached to this document - one for the pricing of goods, one for the pricing of tariff and passenger costs, and one for collecting information on the locality.

Cleaning operations

Data editing was done in the field by supervisors, and double data entry was carried out by Pentax. After receiving data from Pentax, NORC assisted with reconciliation between the first and second entries. After reconciling the data, NORC carried out significant data cleaning, including some imputation of values for missing observations. For a detailed explanation of data editing and cleaning, please refer to the attached “Phase 1, Baseline Findings” report. For the raw dataset receioved by NORC from Pentax, see the attached "Raw Data". For SPSS scripts detailing cleaning done on the dataset, see "SPSS Scripts".

This survey focuses on many different issues including, lowering the voting age, approval of Eisenhower, prefer work for man or woman, US defense, increase tariffs, taxes, favorite TV show, party preference and past voting behavior.

German-speaking resident population aged 16 and over

This poll is part of a continuing series of monthly surveys that solicit public opinion on the presidency and on a range of other political and social issues. Respondents were asked to give their opinion of Bill Clinton and his handling of his job as president and to comment on the relationship between the United States and Japan with an emphasis on a possible trade war and tariffs. Respondents were asked to forecast the greatest economic power in the future and to identify the United States' most important partner in the past and future 50 years. Other topics examined in detail included the television and movie rating systems, the role of sex and violence in popular culture, and the government's role in regulating movies and television programs. Those queried also answered questions on Whitewater and on the fear of terrorism in the United States. Background information on respondents includes voter registration status, political party, political orientation, education, age, sex, race, and family income.

During a January 2025 survey, most of Mexican respondents stated that they think it's quite possible that Trump will impose tariffs on Mexico's goods and that the Mexican economy will be hurt a lot by those tariffs

Monitoring the effects of tariff raises in public transport within the framework of the general mobility developments. This description comprises the third wave of the longitudinal mobility survey ( longitudinaal verplaatsingsonderzoek ). Subsequent waves will be stored under different study numbers. The survey monitors ( changes in ) transportational behaviour, mobility and effects of raising tariffs for public transportation. Data were gathered by questionnaire and diaries, describing all mobility during one week. Detailed data were gathered on: family composition, financial situation of family, working hours, commuting, travelling allowances, car, train, use of reduced fare cards for public transport. This wave consists of seven files, containing family-data( A=SPSS-file, D=raw data ), family member-data ( B=SPSS-file, E=raw data ), transfer-data( C=raw data ), week-matrices ( F=raw data ) and commuting data ( G=raw data ) respectively. Background variables: basic characteristics/ residence/ household characteristics/ occupation/employment/ income/capital assets/ education/ consumption of durables

The majority of businesses in Japan were affected by the tariffs announced by the Trump administration, according to a survey conducted in April 2025. While **** percent of respondents stated that they would reduce their exports to the United States from overseas branches, the share that planned a reduction of exports from Japan was ********************.

The Chicago Council undertakes a large-scale public opinion study every two years that compares American and international public opinion on a wide range of important international issues. A significant part of each biennial survey is additionally dedicated to examining a timely theme. The theme of the 2006 survey was, "The Rise of China and India." This data collection presents a unique comparison of international attitudes on how the emergence of China and India as economic dynamos and claimants to great power status will affect the global economy, international security, and politics. Moreover, this study sought to assess American public opinion (Part 1, Public Opinion Survey, United States) on a variety of challenges facing the United States today including international terrorism, nuclear proliferation, conflict in the Middle East, the rising economic and political power of Asia, economic competition from abroad, and threats to energy supplies and the environment. This data collection also provides an understanding of how the Chinese (Part 2, Public Opinion Survey, China) and Indian (Part 3, Public Opinion Survey, India) publics view their nations' international challenges and opportunities and their respective roles as emerging great powers. Parallel surveys were also conducted in Australia (Part 4, Public Opinion Survey, Australia) in conjunction with the Lowy Institute for International Policy, and in South Korea (Part 5, Public Opinion Survey, South Korea) in conjunction with the East Asia Institute. Demographic variables include race, age, gender, religious affiliation, highest level of education, and political identification.

Abstract

Social Impact was contracted by MCC to develop and conduct an evaluation of the Malawi Compact. Specifically, SI has been tasked to “assess the program design and implementation to develop the most rigorous evaluation design feasible, whether it is a performance or impact evaluation, and identify the most appropriate evaluation methodology feasible given the context.” Efforts to identify a research design that would allow for a rigorously defined counterfactual were unsuccessful, and as a result this design document outlines plans for a rigorous performance evaluation that will aim to measure key outcome indicators early on in the Compact, midway through, and at the end of the Compact, as well as track changes over time. This evaluation is designed to address the core questions of the evaluation (Table 1) Since the proposed design is a performance evaluation, it is important to note that it may not be possible to state with confidence how the power sector in Malawi has changed (or not changed) as a result of the Compact, as it will not be possible to control for other potential causes of change. In some cases, however, it may be feasible to identify and potentially rule out alternative explanations. The inability to define a counterfactual requires a reformulation of some of the initial evaluation questions originally proposed by MCC, including some core questions included in the SI-MCC contract. In addition, the Evaluation Assessment Report revealed that both SI and MCC had substantial concerns with regard to the original research questions proposed in Social Impact's contract. This is natural given the way that interventions change over time, and that the proposed questions should be feasible to answer based on the data that can be collected as part of the evaluation. Based on SI's comprehensive desk review, information gathered during the scoping trip, and frequent communication with MCC and MCA-M, the SI evaluation team has developed research questions and research approaches for the PSRP and the IDP project components, as proposed in Tables 2 and 3, respectively. The original questions and the suggested modifications for each question are presented in the Appendix.

Research Questions Through a rigorous performance evaluation, the evaluation design aims to answer the following core evaluation questions and several complementary research questions:

1. What declines in poverty, increases in economic growth, reductions in the electricity related cost of doing business, increases in access to electricity, and increases in value added production are observed over the life of the Compact?
2. What were the results of the interventions - intended and unintended, positive or negative?
3. Are there differences in outcomes of interest by gender, age and income? Sex and income disaggregated information for businesses and households will be pursued to the extent possible.
4. What are the lessons learned and are they applicable to other similar projects?
5. What is the likelihood that the results of the Project will be sustained over time?
6. At the household level, the evaluations shall focus on the following program/project/activities impacts on household and individuals: income; expenditures, consumption and access to energy; individual time devoted to leisure and productive activities.
7. At the enterprise level, the evaluation shall focus on the potential impact of the program/project/activities on: business profitability and productivity; value added production and investment; employment and wage changes; energy consumption and sources of energy used; business losses.
8. At the regulatory, institutional and policy level, the evaluation shall explore the potential impacts of the program/project/activities on: utility operating costs and losses; financial sustainability; private investment, particularly in generation; expansion of electricity access for customers, particularly the poor.

To answer these questions, the evaluation design will leverage diverse research methodologies with different timelines for data collection. The evaluation design can be broken into three main parts, albeit with some overlap:

· IDP evaluation: The IDP design focuses primarily on an intensive metering effort to measure the technical benefits of the project, including changes in energy delivered, outages, and quality. This will be complemented by focus groups with residents of beneficiary communities. · PSRP evaluation: The PSRP design incorporates five data collection activities, including: (1) quantitative indicators from the M&E Plan and Malawi Energy Regulatory Authority (MERA) key performance indicators, (2) workflow analyses with relevant units, such as billing and procurement, (3) a series of largely qualitative research activities (with some mini-surveys included), (4) a proposed survey of Electricity Supply Corporation of Malawi (ESCOM) employees, and (5) the PSRP process evaluation, focused on implementation and achievement of implementation milestones and outputs will be folded into the PSRP data collection activities. · Enterprise survey: A panel survey of businesses will be used to evaluate both the PSRP and the IDP.

IDP Evaluation Design Design Overview We propose that the IDP evaluation consist of two major parts: (1) intensive metering to determine technical benefits, and (2) focus group discussions with beneficiaries. In addition, some of the activities conducted as part of the PSRP evaluation - specifically work flow analyses of response to outages - will also address IDP benefits made possible by the supervisory control and data acquisition (SCADA) systems.

PSRP Social Impact proposes five data collection activities for the PSRP evaluation: (1) quantitative indicators from the M&E Plan and MERA key performance indicators, (2) workflow analyses with relevant units, (3) largely qualitative research activities (with some mini-surveys included), (4) a survey of current ESCOM employees, and (5) process evaluation. These activities will occur in three phases: at baseline (to be conducted as soon as possible), at midline, and at the end of the Compact. The evaluation will seek to identify changes over time and then consider the extent to which any observed improvements can be attributed to Compact activities.

Geographic coverage

Metering - South and Central Transmission backbone investments; North transmission; Lilongwe; New substations

ESCOM survey - national, will target urban employees living near Blantyre, Lilongwe, or Mzuzu.

Enterprise survey - will mainly focus on Lilongwe, will have data for Mzuzu and Blantyre as well.

Analysis unit

Individuals, households and businesses.

Universe

The study population is in the process of being finalized with MCC and MCA-Malawi. The focal points for the evaluation will include ESCOM staff in Lilongwe, Blantyre and Mzuzu, staff at MERA and MoE, enterprises, and households.

Sampling procedure

1. Enterprise Survey

A sampling frame of businesses can be developed from ESCOM's customer records. There are currently 832 MD customers in the ESCOM network. Of these, 448 customers are concentrated in the South; there are 310 customers in the Central region; and there are mere 66 in the North. Given the relatively low number of MD customers, it will be necessary to expand the population of interest to three-phase commercial connections, of which there are 5,389 in the ESCOM network.

The sampling strategy for the enterprise survey is yet to be finalized. Although all business consumers are identified as beneficiaries of the Compact, the benefits might vary across many of these businesses. To focus research efforts as per discussions with MCC and Compact stakeholders, non-businesses, such as government agencies, hospitals, and schools will be dropped from the sampling frame. This list may be further modified once an ongoing ESCOM customer verification program is complete which will yield a geo-referenced location for each enterprise customer. The survey will benefit enormously from this customer verification project.

Sampling could be based on a random sample from among this population; however, it might be desirable to oversample certain subgroups to ensure the evaluation's ability to generalize about sub-populations of interest and compare across these subgroups. The evaluation team initially proposed ensuring representative samples of the degree of expected Compact benefits; however, Compact stakeholders have raised concerns that it will be difficult to distinguish among beneficiaries. There are several additional variables that could be given priority in determining the evaluation's approach to sampling. These include: · Geographical location: South, Central, North · Industry type: manufacturing, agriculture, or services · Electricity consumption at baseline: MD, three-phase customers · Quality of service at baseline: industrial park customer, non-industrial park customer

Exact sample size calculations will be performed when the uncertainty about the sampling approach is resolved. However, if we assume that the evaluation will seek to make comparisons across two subgroups (e.g., high/low beneficiaries or higher/lower consumption), then the evaluation would require a survey of 1,000 enterprises across both these sub-groups in order to measure a minimum detectable effect size of 0.18 standard deviations. Given that this will be a panel study that will track the same businesses over nearly a five year time period, it is likely that there will be a high rate of attrition as businesses either fail or decline to participate in future iterations of the survey. As such, the evaluation team recommends adjusting this estimate by an additional 25% to account for expected attrition from

Monitoring the effects of tariff raises in public transport within the framework of the general mobility developments. This description comprises the sixth wave of the longitudinal mobility survey ( longitudinaal verplaatsingsonderzoek ). Subsequent waves will be stored under different study numbers. The survey monitors ( changes in ) transportational behaviour, mobility and effects of raising tariffs for public transportation. Data were gathered by questionnaire. Diaries had to be filled out, describing all mobility during one week. Detailed data were gathered on: family composition, financial situation of family, working hours, commuting, travelling allowances, car, train, use of reduced fare cards for public transport. This wave consists of five files, containing family-data( A=SPSS-file, D=raw data ), family member-data ( B=SPSS-file, E=raw data ), transfer-data ( C=raw data ) respectively. Background variables: basic characteristics/ residence/ household characteristics/ occupation/employment/ income/capital assets/ education/ consumption of durables