“While individually computing the trade deficit effects of tens of thousands of tariff, regulatory, tax and other policies in each country is complex, if not impossible, their combined effects can be proxied by computing the tariff level consistent with driving bilateral trade deficits to zero. If trade deficits are persistent because of tariff and non-tariff policies and fundamentals, then the tariff rate consistent with offsetting these policies and fundamentals is reciprocal and fair” 1
# Computations based on US census data as of 3 April 2025, at https://www.census.gov/foreign-trade/balance/index.html
raw_data=readr::read_csv(file.path(path_data, "raw_data.csv"))
raw_data %>% format.dt.f(.)The calculation of reciprocal tariff rates is not a complex piece of trade economics.
Here is the science/math behind it: - It assumes that all import goods have elasticity of \(4\). - It also assumes tariff passthrough rate at \(0.25\%\) (i.e. \(25\%\) of the cost will be passed to consumer, the exporter will eat the rest. )
Then it uses the formula: \[Rate = \frac{Deficit}{(\text{Import Elasticity} \times \text{Passthrough Rate} \times \text{Imports})}\]
reciprocal_tariffs_calculations=raw_data %>%
filter(year == 2024) %>%
transmute(
Country=CTYNAME,
Good_imports = IYR/1000, # US imports
Good_exports = EYR/1000, # US exports
Good_deficit = (IYR-EYR)/1000,
# Deficit_percentage = Good_deficit/Good_imports*100,
Deficit_percentage = Good_deficit/(4*0.25*Good_imports)*100,
# Tariffs charged to the US (%)
Tariffs_charged = ifelse(Deficit_percentage>10, Deficit_percentage, 10),
# Reciprocal Tariff Rate = (Deficit/(Import Elasticity*Passthrough Rate*Imports)
Reciprocal_rate = 0.5*Tariffs_charged # But then they further divided it by 2, to
# basically slow the impact to the economy. And that's how they created it.
)Keep in mind that constant price elasticity is rare. It changes over price levels and macro or other factors. Same elasticity for all products is impossible. Each product has a different behavior. Moreover, each product in a different country or market segment has a different pricing behavior and, therefore, elasticity. Assuming that only \(25\%\) of the increased cost will be passed to the customer is unrealistic. First, of all this will differ per product, and second, it is unrealistic to believe that suppliers will absorb the biggest cost. If this is indeed the theoretical foundation behind the tariff increases, then my take is that there is no foundation to justify them; there is just an intent to increase them.
reciprocal_tariffs_calculations %>%
filter(Country == "Dominican Republic") %>%
format.dt.f(.)The Dominican Republic has been hit with a \(10\%\) tariff. Without the minimum \(10\%\) baseline, the White House formula would produce a negative tariff result. So much for the special relationship!
selected_countries=c("China","European Union","Vietnam","Taiwan","Japan","India",
"Korea, South","Thailand","Switzerland","Indonesia","Malaysia",
"Cambodia","United Kingdom","South Africa","Brazil","Bangladesh",
"Singapore","Israel")
selected_tariffs=reciprocal_tariffs_calculations %>%
filter(Country %in% selected_countries)
selected_tariffs %>% format.dt.f(., 20)The Trump tariff formula is a policy for making the decision for setting the tariff. It is a simple form of policy function approximation which I suspect has received no analysis, either theoretical, or through computer simulations, or field experience.
Many others are guided by history, such as the bad experience in the 1930s with the Smoot Hawley tariffs (see https://www.instagram.com/p/DFd183svLsy/)
The most thoughtful people think about the ramifications, considering the impact on prices and the behavior of other countries. This is a direct lookahead approximation which requires planning into the future, a capability that is often associated with higher intelligence.