About the Household Impacts of Tariffs (HIT) Simulation Tool
The Household Impacts of Tariffs (HIT) simulation tool enables users to simulate how changes in import tariffs impact the incomes of households across the income distribution. The website provides estimates of (i) price changes induced by tariff reforms, and (ii) the resulting impact on the real income of households in different percentiles of the income distribution via their impact on (iii) the cost of consumption and (iv) their incomes using detailed data on households’ income and consumption portfolios derived from representative household surveys harmonized with tariff data.
There are two versions of the tool:
- A basic version in which users can select one proportional tariff change for all products, which is ideal for assessing the impacts of tariff reform for a particular product group, an across-the-board reduction in tariffs, or full-scale import tariff liberalization.
- In addition, there is an advanced version in which users can select different tariff changes for as many as 53 different agricultural products. This version is suitable for users who wish to simulate the impacts of more elaborate tariff reforms.
The methodology for simulating the first-order distributional impacts of tariff reforms is discussed in detail in Artuc, Porto, and Rijkers (2019), but the basic logic is as follows: since households in different parts of the income distribution consume different goods and derive their income from different sources, price changes resulting from a change in tariffs will impact different household differently and thus have distributional implications. When tariffs are reduced (increased), households typically face lower (higher) prices for consumption goods, but they may also face a reduction (increase) in their incomes when they are selling such goods. Whether, and to what extent, households benefit from the change in a tariff levied on a particular product thus depends on the balance of these two forces, i.e. whether a household is a net consumer or producer of a particular good. The overall impact on a given household is simply the sum of the product-specific impacts.
The analysis proceeds in two steps:
- Estimating the impact of a change in tariffs on prices.
- Assessing how much the resulting price changes impact the cost of consumption and income of different households; the sum of these impacts is how much household’s real income changes.
It should be noted that these simulations only measure the first-order, i.e. short-run, impacts of tariff liberalization and do not capture second-order adjustments such as changes in the availability of products, changes in consumption patterns, productivity gains arising through increased availability of intermediates, etc., which may well dominate in the medium- to long-run. In addition, our analysis assumes perfect passthrough of changes in tariffs to prices, though different pass-through rates can in principle be accommodated by making adjustments to the selected tariff changes.
To perform the simulations the tool relies on detailed data on household expenditures and income sources derived from representative household surveys harmonized with tariff data from TRAINS. For each percentile of the income distribution, the database contains for each of the 53 products covered by the data the average budget and income shares across households in that percentile. These data can be downloaded here:
The HIT database does contain not the World Bank Group’s official poverty data, which can be found on the PovcalNet website. Note also that the HIT consumption aggregates may differ from those in PovcalNet because the methodology used to calculate aggregate consumption differs from that of PovcalNet. To give a few examples, the HIT consumption aggregate includes expenditures on durable goods, while PovcalNet aggregates typically aim to capture the rental value of durables. As another example, the HIT data includes all health expenditures, whereas health expenditures are not uniformly treated in PovcalNet. Note also that we are scaling up average expenditure per capita to match up national accounts estimates. Specifically, we set mean expenditure per capita equal to GDP per capita in constant 2010 US dollars.