Calculating the United State’s ‘reciprocal’ tariffs

R-bloggers 2025-04-04

[This article was first published on R-Programming – Giles Dickenson-Jones, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here)
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Soon after Trump’s tariffs were announced, it was noted the ‘reciprocal’ tariffs looked suspiciously like the US trade deficit divided by imports.

Ever the skeptic, I couldn’t believe it could be this simple, so I decided to check it out myself with the help of R and UN Comtrade data. Here’s my answer, neatly documented in R code.

If you’re interested in reproducing this analysis you’ll need to get an API key for the comtradr package.

Code block: project setup:

#load packageslibrary(googlesheets4)library(tidyverse)library(countrycode)library(comtradr)#set comtrade api keyset_primary_comtrade_key(ref_comtrade_api_key)ref_gsheet_url<-"https://docs.google.com/spreadsheets/d/1AbPFX21KKfiCr8WWA6fwfPVKAjE5MUCzdWVitV0ZuWM/edit?usp=sharing"#read data from google sheet dta_us_tariffs<-read_sheet(ref_gsheet_url)#add countrycodesdta_us_tariffs<-  dta_us_tariffs |>   mutate(iso3c= countrycode(sourcevar=country, origin="country.name", destination="iso3c"))#assign _KS as as code for Kosovo as per Comtrade country code list (KSV is also used by some providers)dta_us_tariffs[dta_us_tariffs$country=="Kosovo","iso3c"]<-"_KS"#create reference list of focus countriesref_focus_countries<-dta_us_tariffs$iso3c # get bilateral trade data for US dta_comtrade <- ct_get_data(  reporter = 'USA',  partner=dta_us_tariffs$iso3c,  commodity_code = 'TOTAL',  start_date = 2024,  end_date = 2024,  flow_direction = c('import','export'))# select focus variables and round to billion USDdta_comtrade<-dta_comtrade |>   select(ref_year,partner_iso,flow_desc,fobvalue) |>   mutate(fobvalue= fobvalue/10^9) # Pivot dataframe by flow typedta_comtrade<-dta_comtrade |>   pivot_wider(names_from=flow_desc, values_from = fobvalue)#calculate trade balancedta_comtrade<-dta_comtrade |>   mutate(trade_bal= Export- Import,          trade_bal_to_m_ratio= round(trade_bal/Import,2)*100)#join comtrade data with tariff listingdta_us_tariffs_and_trade_flows<-left_join(dta_us_tariffs,dta_comtrade, by=c('iso3c'="partner_iso"))

There’s more I’d like to do with this data, but for now I thought I’d share my code and the answer: yes. The reciprocal tariffs look almost identical to the trade balance to imports ratio.

@carlbergstrom.com has a great thread (skeet?) on this on Bluesky.

Code block:

#create filtered dataframe where tariff > standard rate#drop EU countries as individual reciprocal tariffs weren't published dta_plt_us_tariffs<- dta_us_tariffs_and_trade_flows |>  filter(us_tariffs_applied >10,           EU == "N") #plot where tariff != reciprocal tariffplt_us_tariffs<-ggplot(data=dta_plt_us_tariffs,                       aes(y=us_claimed_reciprocal_tariff,             x=trade_bal_to_m_ratio))+  geom_text(aes(label =iso3c), size=2)+  theme_minimal()+  labs(x= "Imports / Trade Balance (%)",       y="Announced 'Reciprocal' Tariff")plt_us_tariffs

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