GENDER AND INCOME INEQUALITY IN
UNITED STATES TARIFF BURDEN
Arthur Gailes
Tamara Gurevich
Serge Shikher
Marinos Tsigas

ECONOMICS WORKING PAPER SERIES
Working Paper 2018–08–B
500 E Street SW
Washington, DC 20436
August 2018

Office of Economics working papers are the result of ongoing professional research of USITC Staff and are solely meant to represent the opinions and professional research of individual authors. These papers are not meant to represent in any way the views of the U.S. International Trade Commission or any of its individual Commissioners. Working papers are circulated to promote the active exchange of ideas between USITC Staff and recognized experts outside the USITC and to promote professional development of Office Staff by encouraging outside professional critique of staff research. Please address all correspondence to Tamara.Gurevich@usitc.gov or Serge.Shikher@usitc.gov.

Gender and Income Inequality in United States Tariff Burden
Arthur Gailes, Tamara Gurevich, Serge Shikher, Marinos Tsigas
Office of Economics Working Paper 2018–08–B
August 2018

Abstract

The combination of different tariff rates across products and different consumption patterns across households results in different tariff burdens across consumer groups. We investigate the distribution of tariff burden among U.S. households of different incomes and consumers of different genders. As a share of total household consumption expenditure in 2015, the tariff burden was a nearly constant 0.25 percent across all income deciles, meaning that tariffs act as a flat consumption tax. Since a flat consumption tax is a regressive tax on income, tariffs fall disproportionately on the poor. Across genders, we find large differences in tariff burden. Focusing on apparel products, which were responsible for about 75% of the total tariff burden on U.S. households, we find that the majority, 66%, of the tariff burden was from women’s apparel products. In 2015, the tariff burden for U.S. households on women’s apparel was $2.77 billion more than on men’s clothing. This gender gap grew about 11% in real terms between 2006 and 2016. Arthur Gailes, Haas Institute, UC Berkeley arthurgailes@berkeley.edu Tamara Gurevich, Research Division, Office of Economics, USITC tamara.gurevich@usitc.gov Serge Shikher, Research Division, Office of Economics, USITC serge.shikher@usitc.gov Marinos Tsigas, Research Division, Office of Economics, USITC marinos.tsigas@usitc.gov ## Gender and Income Inequality in United States Tariff Burden August 15, 2018 Abstract The combination of different tariff rates across products and different consumption patterns across households results in different tariff burdens across consumer groups. We investigate the distribution of tariff burden among U.S. households of different incomes and consumers of different genders. As a share of total household consumption expenditure in 2015, the tariff burden was a nearly constant 0.25 percent across all income deciles, meaning that tariffs act as a flat consumption tax. Since a flat consumption tax is a regressive tax on income, tariffs fall disproportionately on the poor. Across genders, we find large differences in tariff burden. Focusing on apparel products, which were responsible for about 75% of the total tariff burden on U.S. households, we find that the majority, 66%, of the tariff burden was from women’s apparel products. In 2015, the tariff burden for U.S. households on women’s apparel was$2.77 billion more than on men’s clothing. This gender gap grew about 11% in real terms between 2006 and 2016.

JEL codes: F10, F14, D12, D63

Keywords: non-homotheticity, gender bias

### 1 Introduction

Tariffs have generally been decreasing around the world in the last several decades, but still remain a sizable cost of international trade. Even in the United States, generally a low-tariff country, tariffs continue to be imposed on the majority of goods coming from most countries. In 2015, the average applied U.S. tariff was around 1.5%.1

Behind a relatively low average U.S. tariff, there is a great variation of tariffs across goods. For example, some apparel imported to the U.S. has applied tariffs as high as 31% while other apparel items have low or zero tariffs.2 At the same time, consumption patterns vary across different groups of consumers. For example, men and women tend to consume different sets of products. People with different incomes also tend to consume different baskets of goods: poorer households spend a larger share of their total expenditures on necessities while wealthier households tend to purchase more luxury goods (Henry2014). Therefore, different groups of consumers carry different shares of the tariff burden.3 Equivalently, different groups of consumers would get different benefits from the removal of tariffs. Across some groups, these differences are small. Across other groups, these differences are significant. In this paper, we report large differences in tariff burden across genders in the United States.

In order to calculate tariff burdens we combine data on tariffs with information on consumption patterns of different consumer groups, for example consumers of different incomes or genders. We then calculate the reduction in the cost of the consumption basket for each consumer group that can be attributed to the removal of tariffs. The reduction in the cost of the consumption basket is the tariff burden. Our focus is on the consumer side, so we do not study the effects of tariff on wages.

The fact that U.S. tariffs rates are different for different groups of consumers has been previously documented. Gresser (2002) and Moran (2014) document that average tariffs rates are different for rich and poor U.S. consumers. Barbaro (2007) and Taylor and Dar (2015) provide an overview of the unequal U.S. tariff rates for men’s and women’s apparel. Fajgelbaum and Khandelwal (2016) use a structural gravity model with nonhomothetic preferences to estimate gains from trade for consumers with different incomes. They find that gains from trade are higher for poorer consumers because they spend a higher share of their income on traded goods. Furman, Russ and Shambaugh (2017) calculate tariff burden on U.S. consumers in different income groups and find that U.S. tariffs act as a regressive income tax.4

In this paper, we also examine the tariff burden on U.S. consumers with different levels of income. Similar to the previous literature, we find that poor consumers pay a greater share of their income as tariffs. However, unlike the previous literature we also look at tariff burden as a share of consumption spending. We find that the tariff burden is about the same as a share of consumption spending for consumers in different income deciles. Therefore, U.S. tariffs act as a flat consumption tax. Since poor consumers spend a much greater share of income than rich ones, the tariffs act as a regressive income tax, just like a sales tax.5 Thus, we extend the existing literature by providing this additional prospective on the tariff burden.

Our main contribution, however, is the analysis of tariff burden on men and women. We find significant gender differences in tariff burden, which come from several sources. First, the average tariff rates on the women-specific products are higher than the average tariff rates on men’s merchandise imports. Most of the tariff burden in the U.S. comes from apparel products, and while the average applied U.S. tariff on men’s apparel is about 12%, the average applied U.S. tariff on women’s apparel is about 15%. Second, U.S. consumers spend twice as much money women’s clothing than on men’s clothing and the vast majority of this clothing is imported. The combination of higher tariff rates and and greater spending on imported goods means that women carry a significantly higher share of total tariff burden compared to men.

### 4 Results

In this section, we present the results of our analysis of the tariff burden across households with different income levels. We also present the results of our analysis of the tariff burden across genders.

#### 4.1 Tariff burden across income deciles

We begin by replicating the results of Furman et al. (2017) using our data. We analyze the effects of tariff reduction on 20 final consumer goods that are subject to significant U.S. tariffs. We calculate the burden of tariffs on households in ten income deciles using the methodology described in Section 2.3 and assumptions about price responses described in Section 2.4.1. Our results are similar to Furman et al. (2017), but about 20% smaller since we focus only on products with significant tariffs.17 Our tariff burden estimates are shown on Figure 2 as blue bars. The bars show the tariff burden for each of the ten household deciles under the two alternative assumptions about price changes for domestic goods, with the top end representing a 50% response of domestic prices to tariffs and the bottom end representing a no response.

In addition to assuming exogenous price changes, we also solve for price changes using a CGE model, as explained in Section 2.4.2. The counterfactual experiment simulated by the CGE model involves eliminating tariffs on 23 goods (20 consumption goods and 3 intermediate goods). The experiment is a comparative static one. The resulting estimated tariff burdens are shown as orange dots on Figure 2. As evident from this figure, tariff burden estimates from the CGE model are lower than the estimates from our two assumptions about exogenous price changes because the tariff pass-through to prices of imported goods in the USAGE model is below 100%, which is consistent with the literature.

The annual tariff burden, calculated using the price changes estimated by the CGE model, varies from $41 for the poorest households to$233 for the richest households. Therefore, the tariff burden, in dollars, is increasing in income: wealthier households pay more due to tariffs because they spend more than poorer households. On average, each U.S. household pays $96 in tariffs per year. For the U.S. population, the poorest 10% of the U.S. households face a$525 million tariff burden. The burden of the richest 10% is nearly $3 billion. Total tariff burden for all U.S. households is$12.3 billion.18 Table C1 shows the distribution of tariff burden across all income deciles.

We also calculate the effects of tariffs on the consumer price index faced by households in different income deciles. We use the methodology described in Section 2.2 and price changes estimated by the comparative static analysis from the USAGE model. The change in the price index represents the change in the purchasing power of the households. It also represents the share of tariff in household expenditure. The results are shown as the blue bars on Figure 3. They show that as a share of total household consumption expenditure, the tariff burden is flat at about 0.25 percent across all income deciles.19

This information provides a new view of tariff burden across income deciles. Previous literature found that tariffs act as a regressive (income) tax. Our results show that U.S. tariffs act as a flat consumption tax. Since a flat consumption tax is a regressive tax on income, our results do not contradict existing literature, but provide additional information for the analysis.

#### 4.2 Tariff burden across genders

In this analysis we focus on the apparel sector since we observe significant differences in tariff rates on gender-specific products in that sector and because about 95% of all tariff burden on apparel products comes from gender-specific products. In 2015 the average tariff rate for women’s apparel was 14.9%, but it was only 12.0% on men’s apparel.20 At the same time, households spend about 0.7% of their total annual expenditure on men’s apparel, while spending over 1.2% on women’s apparel (U.S. Bureau of Labor Statistics (BLS)2016).

As in the previous section, we estimate tariff burdens using the methodology described in Section 2.3 and either exogenous price changes, calculated under two alternative assumptions about the effects of tariffs on domestic goods prices, described in Section 2.4.1, or endogenous price changes, estimated by the CGE model in a comparative static simulation.

Total tariff burden on apparel products (using CGE model results) is $8.9 billion, nearly 75% of the total tariff burden of the U.S. households. However, this burden is not equally distributed between men and women. Tariff burden on women’s apparel is$5.8 billion (66% of total apparel burden), compared to men’s apparel burden of $3.1 billion. In other words, the burden of women-specific apparel tariff is nearly twice the amount of the burden of mens-specific apparel tariff. The orange points on the right panel of Figure 4 shows that in 2015 alone, U.S. consumers paid nearly$2.77 billion more due to tariffs when purchasing women’s clothing than men’s.

The tariff burdens estimated using exogenous price changes are shown on Figure 4 as blue bars, with the top end representing a 50% response of domestic goods’ prices to tariffs and the bottom end representing a no response. The tariff burden on women’s apparel ranges between $69 and$86 per household, while the tariff burden on men’s apparel ranges between $33 and$42 per household in 2015. For U.S. population, the tariff burden on women’s apparel ranges between $8.8 billion and$11.0 billion, while the tariff burden on men’s apparel ranges between $4.3 billion and$5.3 billion dollars. As in the CGE simulation results, the tariff burden from women’s apparel is about twice the tariff burden from men’s.

We combine 2006-2016 data on tariff rates, shown in Figure 1, with the 2006-2016 CE survey data to calculate historical trends in men’s and women’s tariff burden from apparel. We calculate the tariff burdens over the years using the set of assumptions about price changes described in Section 2.4.1 (CGE results for these years are not available). We use the midpoint between the two alternative assumptions about the response of domestic goods’ prices to tariffs described in that section.

Figure 5 shows that the tariff burden from apparel has been increasing during these 11 years for both men and women, in real terms. This is due to average apparel tariff increase and spending increase.21

Even though the tariff burden has been growing for both genders, it has been growing faster for women. The difference between women’s and men’s tariff burden has grown from 4.1 billion in 2006 to 4.6 billion in 2016, a change of 11 percent. This growth can be seen in Figure 6.

As we mentioned before, there are two reasons for the difference in tariff burden on women’s and men’s apparel: the average applied tariff rate on women’s apparel is higher than on men’s and women spend more than men on apparel. In Figure 6 we decompose the women-men tariff burden difference into a part that is due to tariff rate differences and a part that is due to spending differences. As evident from the figure, the growth of the gender gap in tariff burden is mainly due to the faster growth of the average applied tariff rate on women’s apparel.

### 5 Conclusion

We investigate the distribution of tariff burden among U.S. households of different incomes and consumers of different genders. To calculate the tariff burden we combine data on tariffs with with information obtained from consumption surveys. Price changes due to tariffs are estimated using either a simple set of assumptions about pass-through rates of tariffs to prices or a computable general equilibrium model, which produces our preferred set of estimates.

We begin by calculating the tariff burden on households in ten income deciles. Since richer households spend more, they also pay more in tariffs. For the U.S. population the poorest 10% of U.S. households pay $535 million in tariff per year while the richest 10% pay$3 billion. As a share of total household consumption expenditure, the tariff burden is a nearly constant 0.25 percent across all income deciles. Therefore, tariffs act as a flat consumption tax. Since a flat consumption tax is a regressive tax on income, tariffs fall disproportionately on the poor.

We then analyze the tariff burden on men’s and women’s products. Since a great portion of gender-specific products are apparel products and apparel products face some of the highest tariffs among U.S. imports, we focus on apparel in our analysis. We find that the total tariff burden from apparel products is about 75% of the total tariff burden on U.S. households. The majority, 66%, of the tariff burden from apparel is from women’s apparel products.

In 2015, the tariff burden for U.S. households on women’s clothing was $2.77 billion more than on men’s clothing. This gender gap has grown about 11% in real terms between 2006 and 2016. We find that two facts are responsible for this gender gap: women spend more on apparel than men and women’s apparel faces higher tariffs than men’s. While the difference in spending contributes more to the overall gender gap in tariff burden, it is the difference in the average applied tariff rate that caused the gap to grow during the recent years. ### Appendix A Additional data information  Table A1: Personal consumption expenditure categories Accessories and parts Alcohol in purchased meals All non-health insurance All other professional medical services Amusement parks, campgrounds, and related recreational services Audio equipment Auto leasing Bakery products Beef and veal Beer Bicycles and accessories Butter Cable and satellite television and radio services Canned tuna Carpets and other floor coverings Cellular telephone services Cereals Cheese Child care Cigarettes Clocks, lamps, lighting fixtures, and other household decorative items Clothing materials Coffee, tea, and other beverage materials Commercial and vocational schools Community food and housing/emergency/other relief services Computer software and accessories Corrective eyeglasses and contact lenses Cosmetic/perfumes/bath/nail preparations and implements Day care and nursery schools Dental services Dishes and flatware Domestic services Educational books Eggs Electric appliances for personal care Electricity Elementary and secondary schools Fats and oils Film and photographic supplies Financial services First-class postal service (by U.S. Postal Service) Fish and seafood Flowers, seeds, and potted plants Foundations and grantmaking and giving services to households Fresh milk Fruit (fresh) Fuel oil Funeral and burial services Furniture Gambling Games, toys, and hobbies Garbage and trash collection Gasoline and other motor fuel Hairdressing salons and personal grooming establishments Higher education Home health care Hospitals Household cleaning products Household linens Household paper products Intercity buses Internet access Intracity mass transit Jewelry Laundry and drycleaning services Legal services Lubricants and fluids Luggage and similar personal items Maintenance and repair of recreational vehicles and sports equipment Major household appliances Medical care and hospitalization Medical laboratories Membership clubs and participant sports centers Men’s and boys’ clothing Mineral waters, soft drinks, and vegetable juices Miscellaneous household products Motor vehicle maintenance and repair Motor vehicle rental Motorcycles Moving, storage, and freight services Musical instruments Natural gas New autos New light trucks Newspapers and periodicals Non-gendered apparel Nonelectric cookware and tableware Nursing homes Other delivery services (by non-U.S. postal facilities) Other Entertainment Other fuels Other household services Other meats Other medical products Other personal business services Other personal care goods and services Other purchased meals Other recreational vehicles Other video equipment Outdoor equipment and supplies Parking fees and tolls Personal computers and peripheral equipment Pets and related products Pharmaceutical products Photo processing Photo studios Photographic equipment Physician services Pork Poultry Prerecorded and blank audio discs/tapes/digital files/downloads Processed dairy products Processed fruits and vegetables Railway transportation Recreational books Religious organizations’ services to households Repair and hire of footwear Repair of audio-visual, photographic, and information processing equipment Repair of furniture, furnishings, and floor coverings Repair of household appliances Shoes and footwear Small electric household appliances Social advocacy and civic and social organizations Social assistance Specialty outpatient care facilities and health and allied services Spectator sports Spirits Sporting equipment, supplies, guns, and ammunition Stationery and miscellaneous printed materials Sugar Sweets Tax preparation and other related services Taxicabs Telecommunication services Telephone and facsimile equipment Televisions Therapeutic medical equipment Tires Tobacco Tools, hardware, and supplies Travel and vacation services Used autos Used light trucks Vegetables (fresh) Veterinary and other services for pets Video cassettes and discs, blank and prerecorded Video media rental Watches Water supply and sewage maintenance Window coverings Wine Women’s and girls’ clothing Table A2: Sectors with significant U.S. tariffs  Sector U.S. tariff${}^{a}$ U.S. TRQ${}^{b}$ Total Food and agriculture Cheese 7.3 8 15.3 Butter 5.8 15 20.8 Raw cane sugar 1.3 28 29.3 Refined sugar 1.6 55 56.6 Beef 1.0 0 1.0 Canned tuna 12.3 0 12.3 All textiles and apparel Fiber, yarn, and threads 5.2 0 5.2 Fabrics 5.0 0 5.0 Carpets and rugs 6.3 0 6.3 Other textile products 5.5 0 5.5 Apparel 12.8 0 12.8 Other manufacturing sectors Ball and roller bearings${}^{*}$ 5.8 0 5.8 Cellulosic organic fibers 4.7 0 4.7 Ceramic wall and floor tiles 6.2 0 6.2 China, fine earthenware, other pottery products 5.3 0 5.3 Cigarettes 6.7 0 6.7 Costume jewelry and novelties 7.5 0 7.5 Leather and allied product manufacturing 10.1 0 10.1 Other pressed and blown glass and glassware 5.3 0 5.3 Pens and mechanical pencils 5.2 0 5.2 Pesticides and agricultural chemicals (excluding fertilizers)${}^{*}$ 4.6 0 4.6 Residential electric lighting fixtures 5.0 0 5.0 Synthetic organic dyes and pigments${}^{*}$ 5.1 0 5.1 Reproduced from Table 1.1 of U.S. International Trade Commission (2017). See the report for details. ${}^{a}$ Measured as an ad valorem equivalent share of the CIF value of imports. ${}^{b}$ Measured as an export tax equivalent. ${}^{*}$ Not included in this analysis. ### Appendix B Consumption patterns across income deciles To illustrate the difference in consumption patterns of households in different income deciles, we calculate a ratio of expenditure shares of the richest and poorest household group for all consumption categories in CE. In Table B1 we show top-5 and bottom-5 ratios of expenditure shares for two groups of consumers. Column 2 of Table B1 shows the ratios of expenditure shares of households in the $9{0}^{th}$ percentile of income distribution to expenditure shares of households in the $1{0}^{th}$ percentile of income distribution, sorted in a descending order. We can see that the richest decile spends an 11-times greater share of total expenditure on photo studios than the poorest decile. The richest decile also spends a much greater share of total expenditure on watches, domestic services, and footwear repair. The poorest decile spends a much greater share of total expenditure on cigarettes, social assistance, funeral services, and home health care than the richest decile. Households in the bottom decile of income distribution spend 20 times more on health care than households in the top decile, as a share of their total expenditure. Column 3 of Table B1 compares households in the bottom of the income distribution to the median household. Expenditure patterns here are similar to the previous case: median households spend a higher share of their total expenditure on luxuries, while poor households spend a higher share on necessities. Table B1: Household expenditure on certain items, by decile  Decile 90/10 Ratio 50/10 Ratio 1 Photo studios (10.77) Photo studios (6.80) 2 Watches (8.95) Footwear repair (5.68) 3 Domestic services (7.97) Jewelry (4.66) 4 Footwear repair (7.91) Therapeutic medical equipment (4.02) 5 Commercial and vocational schools (7.64) New autos (3.62) 74 Men’s apparel (1.13) 77 Women’s apparel (1.12) 104 Women’s apparel (0.79) 110 Men’s apparel (0.76) 147 Tobacco (0.23) Nursing homes (0.21) 148 Cigarettes (0.18) Funeral and burial services (0.18) 149 Social assistance (0.14) Higher education (0.15) 150 Funeral and burial services (0.12) Social assistance (0.13) 150 Home health care (0.05) Home health care (0.01) Source: The U.S. Consumer Expenditure Survey for 2015. ### Appendix C Details on the U.S. tariff burden estimates Table C1: U.S. tariff burdens, by decile  Tariff burden CPI Household Population Decile change, % endogenous exogenous, low exogenous, high in billions 1 0.23$40.52 $64.26$69.67 0.52 2 0.26 $46.61$63.70 $69.07 0.60 3 0.22$53.57 $80.56$87.36 0.69 4 0.25 $71.05$102.55 $111.20 0.91 5 0.20$60.61 $98.29$106.57 0.78 6 0.22 $79.11$126.14 $136.78 1.01 7 0.22$92.07 $132.91$144.12 1.18 8 0.25 $125.06$172.94 $187.52 1.60 9 0.25$155.37 $212.75$230.70 1.99 10 0.26 $233.06$324.87 \$352.26 2.98

Source: The U.S. Consumer Expenditure Survey for 2015. Price changes and associated CPI changes are calculated using methodology described above in Section 3.2.

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*Haas Institute, UC Berkeley; formerly at the U.S. International Trade Commission.

Contact emails: tamara.gurevich@usitc.gov, serge.shikher@usitc.gov. The views expressed in this paper are strictly those of the authors and do not represent the opinions of the U.S. International Trade Commission or of any of its Commissioners.

1This average was obtained using the information from the DataWeb (USITC’s Tariff Information System). The tariff was calculated as the ratio of all duties collected in a year over total charges, insurance, and freight (CIF) values of all imported products reported in that year.

2Highest-tariff HTS10 apparel items include 6104.29.10.50 (women’s blouses, shirts and tops of artificial fibers), 6104.23.00.36 (women’s blouses, shirts and tops of synthetic fibers), and 6110.30.30.25 (girls’ garments imported as parts of playsuits). Lowest-tariff HTS10 apparel items include 6103.23.00.45 (men’s or boys’ shorts of synthetic fibers) and 6103.22.00.70 (men’s or boys’ cotton sweaters).

3“Tariff burden” and, more generally, “tax burden” are common terms used in economic analysis of the effects of tariffs on various population groups and do not express judgment.

4Other papers that investigate the effects of trade policy on consumers with different income levels include Nicita, Olarreaga and Porto (2014), Hottman and Monarch (2018), and Borusyak and Jaravel (2018). Note that unlike some of the other papers in the literature, we do not report whether trade in itself is pro-rich or pro-poor. Rather, we investigate the effects of U.S. tariffs on U.S. households of different income levels.

5A tax that falls disproportionately on the poor is called “regressive” because the tax percentage is declining with income. A tax that falls disproportionately on the rich is called “progressive” or “graduated” because the tax percentage is increasing with income. A tax with a constant percentage is called proportional or flat (true flat).

6We use BLS-provided population weight of each household called F21.

7We use HTS subheadings to identify gender-specific and non-gender-specific items. For example, many accessories, such as gloves and scarves, are non-gender-specific in the HTS.

8We use the UCC to PCE concordance provided by the BLS https://www.bls.gov/cex/cecomparison.htm.

9In total, 23 sectors were identified in U.S. International Trade Commission (2017) as having significant tariffs. These sectors are reproduced in Appendix table A2. Of these 23 sectors, households do not report consumption in 3 sectors: ball and roller bearings, pesticides and agricultural chemicals, and synthetic organic dyes. These 3 sectors are included in the USAGE model simulations, but do not directly feed into household consumption.

10These sectors are responsible for about 80% of the tariff burden (compare our estimates with Furman et al. (2017)).

12Apparel items are listed in chapters 61 and 62 of the HTS.

13These rates correspond to ${\tau }_{Mgs}$, ${\tau }_{Wgs}$, and ${\tau }_{ng}$ described Section 2.1.

15Note that as a result of this level of granularity in data collection, expenditure shares ${s}_{Djt}$ exhibit year-to-year fluctuations due to sampling and measurement error. Therefore, we use the average expenditure shares over 2013–2015.