This paper lays out an approach, and a research agenda, for assessing the impact of carbon pricing on household budgets, and of possible compensatory government transfers that can be financed through carbon-tax revenues. It relies on a rich set of available data and policy models and combines them in a way that is informative for mapping the gains and losses at the household level in the short term as countries transition to a low-carbon economy. A particular focus is on linking information on carbon emissions and consumption patterns (which is needed for quantifying carbon-tax burdens), with income data and tax-transfer policy models (needed for assessing government policies that aim to cushion or offset carbon-tax burdens). The approach is illustrated for a carbon-tax scenario based on a recent proposal in Lithuania. Results confirm that direct burdens from higher fuel prices fall disproportionately on lower-income households. But indirect effects, from higher prices of goods other than fuel, are sizeable and broadly "flat" across the income distribution, which dampens regressivity. Low-income households are also found to respond more strongly to rising prices, reducing their burdens and, hence, regressivity. The total effect is only mildly regressive. Recycling carbon-tax revenues back to households allows considerable scope for avoiding or cushioning losses for large parts of the population, and existing policy models can be used to design compensation measures that facilitate majority support for carbon tax packages.