1. Introduction
Despite various assertions made by President Trump on the purported economic benefits of tariffs, not many empirical studies have shown robust evidence to support these claims. The paper tries to fill in the gap by examining a key set of economic metrics across the time preceding, during, and following tariff implementation, to provide a quantitative evaluation of the events associated with the recently implemented tariffs. Because any tariff policy usually involves at least two countries, our focuses on the metrics include not only the United States, but three other heavily impacted countries, China, Canada, and Mexico, observing the same time to have a cross-country examination for the outcomes. To clarify the scope of the policy under examination, this paper will be analyzing the tariffs that were announced by April 2025. While some measures are built on his first term measures, such as those on aluminum and steel, the 2025 tariffs also target new sectors, including pharmaceuticals and furniture.
During his second presidential campaign, President Trump promised to enact an increased number of tariffs, stating that these tariffs will be beneficial for the US economy, encouraging an increase in the number of US goods that are sold, while decreasing the trade deficits with other major countries. York and Durante (2025) found that the Trump administration’s intent to use tariffs to narrow the trade deficit would reduce both imports and US exports, resulting in little to no change in the deficit. He has also claimed that it will increase the amount of taxes raised and promote the levels of investment. As of February 2025, Canada, Mexico, and China made up 43% of all U.S. imports (Scarsciotti et al., 2025). On February 1, 2025, tariffs on Canada, and Mexico, and China went into effect, though the Canadian and Mexican tariffs saw a temporary 30 day pause on February 3. On April 2, President Trump announced reciprocal tariffs on all imports, with higher rates for countries with trade surpluses like China, South Korea, Japan, and those within the European Union. In response, several countries, notably China and Canada, have implemented their own retaliatory tariffs on US exports.
The United States has been in a trade war with China since President Trump’s first term in 2018, and the conflict has only intensified with the current tariffs.1 Historically, China has seen reduced US demand for its goods upon tariff implementation, but it offset the losses through trade diversion (Ferraro & Leemput, 2019). Tensions have also risen with the European Union and Mexico. During President Trump’s first term, the stock market experienced increased volatility due to the administration’s trade policies and tariff announcements. Concerns about a potential trade war and its impact on global supply chains heavily influenced investor sentiment. Therefore, we think a detailed examination including both regular macroeconomic variables and stock market metrics is a good way to look at events associated with the tariffs from a broader perspective.
2. Methodology
2.1. About Methodology
To have a quantitative evaluation for the economic effects, we’ve chosen a set of key indicators, spanning major macroeconomic variables, broad stock market measures, and specific industries directly affected by the tariffs. We compare their performance before, during, and after the tariff implementation to show potential correlations between the shifts and the timing of the tariffs. We understand the methodology applied in the paper would not be able to draw the causal relationship and thereby, to prove any of the unfavorable shifts are indeed caused by the tariffs, but the data points are evidence to argue against the notion of a straightforward tariff-driven economic gain. Kilumelume et al. (2025) and Thiagarajan, Bender and Metcalfe (2025) both note that tariffs can distort market dynamics and reduce productivity, which aligns with the observed economic shifts. The following sections are structured in the way to observe three key sets of indicators. First, we examined macroeconomic variables such as CPI, GDP, unemployment rate, and PCE. Next, we analyzed broad stock market measurements, focusing on volatility and volume, by comparing their means and standard deviations across different periods and countries, and conducting tests to determine if the changes were statistically significant. Finally, we investigated industry-specific indices to gain insights into the impacts on specific sectors. With this, we can have a holistic view first on general economic performance, then on the core capital market, and last on a set of specific industries heavily influenced by the tariffs.
2.2. Macroeconomics2
Four key metrics were studied: inflation rate, unemployment rate, consumer spending (PCE), and real gross domestic product (GDP). The inflation rate, consumer spending, and GDP were tracked as changes from the previous report date, while unemployment remained as the number reported. Inflation, unemployment, and GDP were expressed as percentage changes, while consumer spending was reported as nominal changes in each country’s respective currency. Data sources for the US included bls.gov for inflation and employment data, and bea.gov for GDP and consumer spending data. For Canada, data was gathered from statcan.gc.ca for inflation, unemployment, and GDP, and from tradingeconomics.com for consumer spending. Mexico’s data for all four metrics was sourced from tradingeconomics.com. For China, inflation, unemployment, and GDP data were obtained from tradingeconomics.com, while consumer spending data came from http://www.stats.gov.cn/.
It is important to note that the data for China’s consumer spending metric is represented by total retail sales reports. This metric does not show the average in month-by-month increases but rather the average of total sales per month. China does not publish household consumption data on a standard basis that allows for short-term analysis. Therefore, for this analysis, China’s monthly consumption is represented by the total retail sales metric. These figures are used as a proxy for household consumption, acknowledging that they exclude services and informal spending. Although this may introduce limitations in cross-country comparisons, this metric should still serve as a fairly representative indicator of consumer trends for China.
Two periods were observed. Period 1, from April 2025 to October 2024 (Q2 2024 to Q3 2024), was chosen to cover the six months leading up to President Trump’s election and establish a baseline for the macroeconomic indicators. Period 2, from November 2024 to April 2025 (Q4 2024 to Q1 2025), was selected to observe the changes in the macroeconomic indicators after President Trump’s election, inauguration, and implementation of tariffs.
The first set of dates in each period corresponds to metrics with reports released monthly, and the second set is relative to metrics with reports released quarterly. The frequency of release of the reports referenced in this study for each country are as follows: monthly reports for the US and China include inflation, unemployment, and consumer spending, while Canada and Mexico report inflation and unemployment. Quarterly reports for the US and China include GDP, while Canada and Mexico report GDP and consumer spending. Means for each metric were calculated across both periods.
2.3. Stock Markets
We choose the volatility and volume to represent broad stock markets dynamics and calculate the returns to measure the growth of capital markets.
For Volatility
Data was gathered from Yahoo Finance for the US (S&P 500), Canada (S&P/TSX), Mexico (IPC MEXICO), and China (SSE Composite) were studied. The study was divided into three periods. Period 1, from 2 months before President Trump’s election (September 10, 2024) to Election Day (November 5, 2024), was chosen to establish a baseline in stock market activity for comparison. Period 2, from Election Day to Inauguration Day (January 20, 2025), was chosen to track possible investor uncertainty post-election, and Period 3, from Inauguration Day to April 15, 2025, was chosen to track stock market activity post-tariff implementation.
Daily closing prices for each stock index were collected for each period, excluding any holidays or special events. Within each individual period, the rate of return was calculated using each daily closing price, and the standard deviation for the return percentages was determined. For days with no available stock price, the closing price was taken for the next available day and calculated with the last available day. Two-tailed F-tests with alpha levels of 0.05 were performed to compare Periods 2 and 3 to Period 1, with adjustments made to exclude outliers in the Shanghai Stock Exchange.
For Volume
Data was gathered from Yahoo Finance for the US (NYSE), Canada, Mexico, and China. Two periods were observed. Period 1, from April 1, 2024 to October 31, 2024, covers the pre-tariff period and was chosen to establish a baseline in trading volume before the tariffs were implemented, encompassing the six months before President Trump was elected. Period 2, from November 1, 2024 to April 30, 2025, includes the post-tariff period and was selected to track the changes in trading volume after the tariffs were implemented, covering the six months following President Trump’s election, inauguration, and the short term after the bulk of the tariffs were put into effect.
The daily trading volume of each index was gathered, and the means for both periods were calculated. Unpaired two sample T-tests with alpha levels of 0.05 were performed to compare the two periods for each country.
For Returns
Data was gathered from Yahoo Finance for the US (S&P 500), Canada, Mexico, and China. We use the daily closing prices to calculate the rate of returns. Meanwhile, two periods were observed. Period 1, from February 4, 2025 to February 11, 2025, was selected to observe the immediate aftermath of the tariffs on China and serve as the pre-announcement baseline for Canada and Mexico. Period 2, from March 4, 2025 to March 11, 2025, reflects the post-announcement stabilization stage for China and presents the market response following Canada and Mexico’s respective tariff announcements.
We use two short, six-day analysis periods to assess the immediate market reactions to the tariff announcements. This timeframe was selected to capture short-term volatility and investor sentiment surrounding the key policy events, while minimizing confounding factors from unrelated macroeconomic developments. Though brief, this structure allows for timely, event-focused analysis and supports country-specific insights. While this structure limits direct cross-country comparison, it provides a useful snapshot of how financial markets responded in the period immediately after the tariffs were announced.
Notably, on March 5 and 6, President Trump paused/postponed automotive and other tariffs on Mexico and Canada, but it should not impact the data significantly, as uncertainty has already been created. The daily closing prices of each index were used to calculate the rate of returns, and then the mean and standard deviation of the rates were calculated. Unpaired two sample T-tests with alpha levels of 0.05 were performed to compare the two periods for each country.
2.4. Returns from Specific Industries3
With the 2018 tariffs, numerous industries saw significant abnormal returns within the first two days, which were exacerbated over the following 20 days (Selmi, Errami, & Wohar, 2020). We chose three major industries in the US impacted by the tariffs to study: building and construction, consumer discretionary, and technology.4 ETFs for each industry were acquired from etfdb.com. The ETFs studied were:
Building and Construction: First Trust RBA American Industrial Renaissance ETF (AIRR), iShares U.S. Home Construction ETF (ITB), SPDR S&P Homebuilders ETF (XHB), Invesco Building and Construction ETF (PKB).
Consumer Discretionary: Consumer Discretionary Select Sector SDPR Fund (XLY), Vanguard Consumer Discretionary ETF (VCR), Fidelity MSCI Consumer Discretionary Index ETF (FDIS), SPDR S&P Retail ETF (XRT), First Trust Consumer Discretionary AlphaDEX Fund (FXD).
Technology: Invesco QQQ Trust Series I (QQQ), Vanguard Information Technology ETF (VGT), The Technology Select Sector SPDR Fund (XLK), VanEck Semiconductor ETF (SMH), iShares U.S. Technology ETF (IYW).
Two periods were observed. Period 1, from February 4, 2025 to February 11, 2025, was selected to observe the immediate impact of tariffs on the industries, providing a baseline for comparison. Period 2, from March 4, 2025 to March 11, 2025, was chosen to analyze the short-term responses and adjustments within the industries following the tariff announcements. These two six-day periods were chosen to capture short-term shifts in sector performance coinciding with the tariff announcements. They allow for assessment of immediate market behavior across the industries studied. Though a tighter time frame typically reduces the chance of coinciding with broader economic developments, it cannot fully control for broader market influences. Thus, results should be interpreted as preliminary signals rather than definitive measures of industry-level impact.
For each day within the samples, the closing prices for the five ETFs within each industry were collected. The average closing price for the five ETFS was calculated by summing the closing prices and dividing them by five (or four for building and construction). Using these averaged closing prices, the rate of return for each day was calculated. The standard deviation and mean for the rate of return over the 6-day periods were also calculated. Unpaired two sample T-tests with alpha levels of 0.05 were performed to compare the two periods for each industry.
3. Findings
3.1. Macroeconomics
Table 1 reflects the relative averages of the unemployment rate and the month-by-month and quarter-by-quarter changes in inflation, GDP, and consumption for each country over the two periods observed.
For the US, the inflation rate increased from Period 1 to Period 2, unemployment rose, GDP growth slowed, and consumer spending increased. This increase in inflation and unemployment, in addition to slowed GDP growth, suggests that the tariffs may have contributed to economic strain. Amiti, Redding and Weinstein (2019) showed that the 2018 tariffs were almost entirely passed through into domestic prices, increasing the costs for US consumers. However, the rise in consumer spending indicates that domestic demand has remained strong. In Canada, inflation rates increased at a slower rate, unemployment rose, GDP growth increased, and consumer spending also increased. Although the increase in unemployment signals to certain sectors seeing adverse events correlated with the tariffs, the slower increase in inflation indicates that Canada was able to mitigate some of the price pressures from the tariffs, and the increase in consumer spending establishes that domestic demand has remained solid. With the transition from inflation to deflation, positive to negative GDP growth, and decreased consumer spending, it appears that Mexico was experiencing significant economic challenges when the tariffs were announced, likely due to decreased demand. In China, there was mixed correlations. On one hand, inflation turned into deflation and the unemployment rate increased, likely due to the reduced export demand and lower prices for goods. On the other hand, China experienced an increased in GDP growth rate, and an increase in consumer spending, suggesting that there is still strong domestic demand that slows for economic growth despite the possible challenges associated with the tariffs.
Table 1. Average changes in macreconomic metrics over 6-month periods by country.
Period |
United States |
Inflation (%) |
Unemployment (%) |
GDP (%) |
PCE (bil. USD) |
1 |
0.14 |
4.1 |
3.05 |
67.7 |
2 |
0.25 |
4.13 |
0.95 |
75.7 |
Period |
Canada |
Inflation (%) |
Unemployment (%) |
GDP (%) |
PCE (mil. CAD) |
1 |
0.19 |
6.39 |
0.4 |
10,105 |
2 |
0.15 |
6.72 |
0.55 |
10,385 |
Period |
Mexico |
Inflation (%) |
Unemployment (%) |
GDP (%) |
PCE (mil. MXN) |
1 |
0.05 |
2.76 |
0.55 |
91,150 |
2 |
−0.14 |
2.48 |
−0.25 |
−166,000 |
Period |
China |
Inflation (%) |
Unemployment (%) |
GDP (%) |
PCE (bil. RMB) |
1 |
0.06 |
5.09 |
1.1 |
3980.47 |
2 |
−0.07 |
5.17 |
1.2 |
4179.67 |
3.2. Stock Market
Volatility
We summarize the means and standard deviations of the returns for each stock index’s closing price in each country across the three observed periods in Table 2 and list the F-test results accordingly in Table 3. The US stock index transitioned from experiencing an average of increasing closing prices to experiencing an average of decreasing closing prices, with increasing volatility in each period. Canada exhibited a similar downwards trend in average closing prices, with volatility also rising over the three periods. The data from these two countries suggest that the tariffs had a negative association with investor sentiment and market stability in the longer term. Mexico experienced a dip in closing prices during the second period, followed by an increase in the third period. Volatility in Mexico decreased in the second period but increased again in the third. In China, closing prices decreased in Period 2 but showed a slight increase in Period 3. This pattern suggests a potential correlation between the implementation of tariffs and market fluctuations, with the timing of these changes reflecting a possible initial negative market response. China experienced the highest level of volatility in Period 1, which decreased in Period 2, and slightly increased in Period 3, suggesting the market was more reactive before the tariffs, and was able to stabilize itself over time after the tariffs were announced.
Table 2. Average rate of returns and spread over 3 months by country.
Country |
Period 1 |
Period 2 |
Period 3 |
Mean |
SD |
Mean |
SD |
Mean |
SD |
United States |
0.13% |
0.66% |
0.01% |
0.81% |
−0.17% |
1.94% |
Canada |
0.15% |
0.50% |
0.04% |
0.62% |
−0.07% |
1.47% |
Mexico |
0.00% |
0.88% |
−0.06% |
0.83% |
0.08% |
1.27% |
China |
0.49% |
1.51% |
−0.08% |
1.09% |
0.02% |
1.26% |
The F-test results indicate significant differences in the variances of stock market returns for the US, Canada, and Mexico between Periods 1 and 3, suggesting increased volatility related to the tariffs. None of the countries studied displayed significant differences in stock market returns between Periods 1 and 2. In China, there was no significant difference between Periods 1 and 2 or Periods 1 and 3. This lack of significant differences between each of the periods indicates that China’s market volatility was less responsive to events associated with the tariffs as compared to other countries.
Table 3. F-test results for volatility.
Country |
Period 1 - Period 2 |
Period 1 - Period 3 |
F-statistic |
P-value |
F-statistic |
P-value |
United States |
1.5062 |
0.1912 |
8.64 |
>0.001 |
Canada |
1.5376 |
0.171 |
8.6436 |
>0.001 |
Mexico |
0.8896 |
1.3036 |
2.0828 |
0.0194 |
China |
0.5211 |
1.9634 |
0.6963 |
1.7584 |
Volume
Table 4 presents the average daily volumes for each stock index across the different countries and periods. Compared to the pre-tariff period, there are notable changes in trading volumes for each country. In the US, the average daily trading volume surged by nearly 1 billion shares, representing an increase of around 25%. Canada experienced a rise of about twenty-five million shares, which is around an 11% increase. China saw a significant boost of over 1.5 billion shares, equating to an increase of approximately 43%. Conversely, Mexico experienced a decline in average daily trading volume by around twenty million shares, which is around a 10% decrease. The data suggests that following the implementation of tariffs, trading volume shifted with notable variation in both degree and magnitude. The substantial increase in trading volumes in the US, Canada, and China suggests heightened market activity, possibly due to increased investor interest. On the other hand, Mexico’s decrease in trading volume might indicate some reduced market confidence or economic uncertainty stemming from the tariffs.
Table 4. Average trading volume over 6-month periods by country.
Country |
Period 1 |
Period 2 |
United States |
3786918054.1 |
4,766,488,250 |
Canada |
231071703.4 |
256306283.7 |
Mexico |
223,440,610 |
201419081.5 |
China |
3,727,251,799 |
5,318,512,605 |
The T-test results in Table 5 show that the US, Canada, and China had statistically significant differences in means between the two periods, indicating notable shifts in trading activity. In contrast, Mexico did not exhibit a statistically significant change, suggesting a more stable trading environment. However, the nominal decline in Mexico’s volume could hint at localized investor uncertainty or sector-specific events associated with the tariffs.
Table 5. T-test results for volume.
Country |
T-statistic |
P-value |
United States |
8.4085 |
>0.0001 |
Canada |
2.9098 |
0.0039 |
Mexico |
1.6009 |
0.1106 |
China |
8.2712 |
>0.0001 |
Returns
Table 6 provides the relative means and standard deviations of the daily percentage changes for each country in the periods studied. This table highlights the short-term response of the stock market, as it compares the week following the implementation of the February and March tariffs for each country. The data indicates that the implementation of tariffs is associated with significant events that occurred in the stock markets of the countries studied and allows for an understanding of market sentiment in the immediate aftermath. Volatility spiked significantly in all countries during their post-announcement periods, with China and the US displaying the highest levels in Periods 1 and 2, respectively. The sharp increase then decline in returns in the US for Period 2 suggests that investors were particularly reactive to the new tariffs with Canada and Mexico, likely worried about the broader economic implications that the March tariffs would bring. In contrast, China’s lowered volatility and general increase in mean returns in Period 2 signal a stabilizing or positive market response. Meanwhile, the decline in returns and rise in volatility in Mexico and Canada indicate a negative market response to the new tariffs.
Table 6. Averages and spread of returns for each week by country.
Country |
Period 1 |
Period 2 |
Mean |
SD |
Mean |
SD |
United States |
0.10% |
0.63% |
−0.71% |
1.58% |
Canada |
0.28% |
0.67% |
−0.26% |
1.18% |
Mexico |
0.60% |
1.03% |
−0.33% |
1.06% |
China |
0.11% |
1.13% |
0.33% |
0.58% |
Table 7 displays the T-test results for each country. While Table 6 highlighted the general increases toward volatility following the tariff implementations, Table 7 reveals that only the US had a statistically significant change in mean returns between the two periods. This reinforces the interpretation that US investors were particularly reactive in response to the trade policies. On the other hand, the lack of statistical significance in Canada, Mexico, and China suggests that the shifts in returns could have been due to random chance, requiring caution in drawing more generalizable conclusions.
Table 7. T-test results for returns.
Country |
T-statistic |
P-value |
United States |
5.0086 |
0.001 |
Canada |
0.8898 |
0.3995 |
Mexico |
1.407 |
0.1971 |
China |
0.3873 |
0.7086 |
3.3. Industry Specific Returns
Table 8 provides the relative means and standard deviations of the daily percentage changes for the average of the ETFs in each industry studied. This table highlights the increased volatility in Period 2 compared to Period 1, as Period 2 experiences significant changes. The building and construction and consumer discretionary industries experienced average decreases in both periods, with more significant decreases in Period 2. This shift may reflect sensitivity to increased costs of imported materials and reduced consumer spending. The technology industry, which initially saw an average increase in February, experienced a notable decrease in March, suggesting a delayed market adjustment that coincided with the tariff timeline. Stackpole (2024) reported that President Trump’s first-term tariffs failed to lower import costs or revive manufacturing jobs, and hurt sectors targeted by retaliation. The increased standard deviations in Period 2 for all industries suggest heightened market volatility and uncertainty during this period.
Table 8. Average rate of returns and spread for each week by industry.
Industry |
Period 1 |
Period 2 |
Mean |
SD |
Mean |
SD |
Building and Construction |
−0.01% |
1.28% |
−0.11% |
1.42% |
Consumer Discretionary |
−0.66% |
1% |
−1.07% |
1.91% |
Technology |
0.36% |
1% |
−0.98% |
2.60% |
Table 9 presents the T-test results for each industry. Although Table 8 had revealed notable shifts and volatility observed for each industry following the tariff implementations, none experienced statistically significant differences in mean returns. This suggests that while the tariffs may have contributed to more fluctuations, the average daily returns did not shift in a consistent enough manner to meet the significance threshold. The industry responses could have been impacted by confounding factors and reveal that increased volatility does not necessarily translate into a meaningful shift in average performance.
Table 9. T-test results for industry returns.
Industry |
T-statistic |
P-value |
Building and Construction |
0.117 |
0.9098 |
Consumer Discretionary |
0.4252 |
0.6819 |
Technology |
1.0756 |
0.3135 |
4. Conclusion
The implementation of tariffs corresponded with varied and significant shifts in the economic indicators and stock market performance of the countries studied. Despite the claims made by President Trump regarding the positive impacts of tariffs for the US economy, the data presented in this paper reveals trends supporting the contrary.
In the United States, while consumer spending has remained strong, the economy has seen increased inflation, risen unemployment rates, and slowed GDP growth, indicating economic strain rather than improvement. Canada showed resilience with rising GDP growth and consumer spending, but also faced higher unemployment and slower inflation increases, reflecting a complex and uneven economic response to the tariffs. Mexico faced significant economic challenges, including deflation, negative GDP growth, and decreased consumer spending, conditions that highlight the severity of its economic strain during the tariff period. China’s indicators were mixed, with deflation and increased unemployment, signaling economic pressure, but also rising GDP growth and consumer spending, suggesting that strong domestic demand may have helped offset external shocks.
The stock markets and industries in these countries also displayed increased volatility and varied responses during the tariff period. The data clearly shows that the tariffs did not result in the intended economic benefits. Instead, they introduced heightened levels of complexity and uncertainty, impacting the different economies and sectors in distinct ways. This reflects the importance of gaining a comprehensive understanding of the broader economic implications of policy decisions like tariffs. While claims can be made to justify these policies, the actual impacts can be complex and may not result in the intended outcomes.
For policymakers considering similar protectionist measures, it is important to note the significant implications of such measures. The observed economic strains and market volatility highlight the complexities of implementing tariffs. The study’s findings revealed that tariffs are associated with varied and significant economic events in different countries, with some showing resilience while others face severe economic challenges. Policymakers should consider the interconnectedness of the global economy and the potential for spillover effects when designing protectionist policies and weigh the potential economic costs against the anticipated benefits, considering both short-term and long-term effects.
However, several limitations must be acknowledged. As the study is purely correlational, causality cannot be established, and thus, all evidence presented should be interpreted with caution. Additionally, the six-day time frame considered may not capture the full extent of events related to the tariffs. This brief period was selected to minimize confounding factors from unrelated macroeconomic developments, but it limits the ability to observe longer-term effects. Furthermore, the replacement of China’s consumer discretionary metric with total retail sales as a proxy for household consumption introduces limitations in cross-country comparison. This metric, while representative of consumer trends, excludes services and informal spending, which may impact the comprehensiveness of the analysis. Future research should address these limitations by incorporating a broader range of metrics, extending the analysis period, and considering external variables to provide a more comprehensive understanding of the tariffs’ impacts.
NOTES
1See Ferraro and Leemput (2019) for how tariffs may impact China’s macroeconomy.
2See Scarsciotti, Ravichandran, Pineault, Gaggar, Engineer and The Capital Markets Strategy Group (2025) for how the tariffs may impact macroeconomic factors in the long-term.
3See Kilumelume, Morando, Newman and Rand (2025) for how tariffs may impact companies’ efficiency.
4See Selmi, Errami and Wohar (2020) to see how tariffs from President Trump’s first term impacted US businesses.