Eve is here. Many people will find this research to be too cold-blooded, given its theme of how households respond to financial crises. Included here is a study of the sharp rise in energy prices in Finland in 2022 at the start of the war in Ukraine due to Russian energy sanctions. Note that unlike the similar affordability crisis in the U.S., which has led to significant increases in health care costs, especially for those who lost Obamacare subsidies, there is no excuse not to buy energy. We further note that this study profiles a consumer cost crisis that is certainly smaller than the one caused by the closure of the Strait of Hormuz, namely both the rise in energy costs and the subsequent rise in food costs. Indeed, if energy prices remain high for a long enough period of time, that would be true, just as the economy goes to the toilet, due to what is politely called demand destruction.
The big finding is that wealthier households have largely responded by simply cutting back on new and expensive energy consumption, while lower-income households have fallen behind on rent and debt payments and have seen their incomes fall across the board.
Written by Rassi Aarvik, Professor of Environmental and Resource Economics, University of Helsinki. Part-time professor at Stavanger University of Resources and Economics. Tuomas Kaariaho, Postdoctoral Researcher, University of Helsinki. Matti Riski, Professor of Economics, Aalto School of Management, Aalto University. and Ivo Vehvilainen, Professor of Economics at Aalto University. Originally published on VoxEU
In a cost of living shock, households have to deal with a decline in purchasing power while at the same time substituting goods whose prices have increased. Therefore, the distributional impact of a price shock depends on the adjustment capacity of households. This column examines how Finnish households responded to Europe’s 2022 energy crisis. Responses varied widely by income, with low-income households having the least potential to reduce electricity use and showing the greatest signs of financial strain. Understanding these responses is important for designing relief policies during times of high energy prices.
Recent debates about the cost of living crisis have understandably focused on the different ways in which households are exposed to price increases. Existing research shows that low-income households spend a larger share of their budgets on necessities such as energy and food, and are therefore more likely to be exposed to cost-of-living shocks (Pizer and Sexton 2019, Soldani et al. 2023, Menyhért 2022).
But exposure is only part of the distribution story. Because cost-of-living shocks combine negative real income shocks with changes in relative prices, households must cope with a decline in purchasing power while purchasing substitutes for goods whose prices have increased. Therefore, the distributional impact of price shocks depends on households’ ability to adjust. This means that while some households are able to cushion the shock by shifting consumption away from more expensive goods, drawing down savings, or providing additional labor income, others have more limited opportunities to respond.
However, surprisingly little is known about these reactions. Identifying them requires household-level data on multiple adjustment ranges, large and possibly exogenous price shocks, and variations that expose otherwise similar households to different price shocks.
A natural experiment with the Finnish energy crisis
Russia invaded Ukraine in February 2022, triggering an energy crisis in Europe. This crisis provides a very clean environment to overcome these empirical obstacles (Ahlvik et al. 2026). First of all, the shock itself was unexpected and large. As Figure 1 shows, electricity prices have increased by up to eight times.
Figure 1 Prices of variable price contracts and two-year fixed price contracts for electricity in Finland
Second, Finland’s rich administrative microdata allows us to directly observe household electricity usage and link it to income, benefits, and payment defaults recorded in courts, making it possible to track adjustments along several margins. Third, it was common for households to sign long-term contracts that fixed electricity rates for a long period of time. Predetermined differences in term contract expiration dates generate quasi-experimental variations in price exposures across households facing the same broad economic environment. This setting allows us to compare otherwise similar households that differ only in their exposure to price shocks.
The impact of energy price shocks varied widely across income groups. Households were adjusted along all four margins: electricity consumption, labor income, payment defaults, and other consumption and savings (Figure 2).
Figure 2 Household-level response to electricity contract expiration
Three results stand out.
The response was heterogeneous. Figure 3 illustrates this heterogeneity by income group. While high-income households responded primarily by cutting back on electricity usage, low-income households were more likely to cut much smaller amounts and adjust to other margins instead. In particular, low-income households were more likely to experience increases in labor income, accumulation of payment defaults, and decreases in other expenditures and savings. Among low-income households, labor income per worker increased slightly, but there was no significant increase in labor force participation. This suggests that the income response was primarily driven by increases in time and effort by already employed workers, rather than by non-workers taking new jobs.
Figure 3 Uneven response to the energy crisis by income group
Expectations helped, but only partially. Those whose contracts expired late in the crisis began reducing their electricity usage before their contracts expired. On average, electricity usage fell by 9%, with about a quarter of the total reductions occurring during the crisis period, i.e. in the months before contract expiration. This effect was larger for higher-income households. The longer forecast period made adjustments easier, but it did not completely remove the financial burden from more vulnerable households. Limited liquidity may explain the reaction. Some middle-income households also experienced an increase in payment defaults, although they suffered less than lower-income households. Payment defaults are on the rise, especially among middle-income households with high debt-to-income ratios, consistent with the idea of a liquidity-constrained middle class. Limited liquidity may partly explain the weaker response in electricity use, as households at the bottom of the income distribution may have fewer opportunities to make energy-saving investments during the crisis than higher-income households.
What the results mean for relief policy
As governments respond to the energy crisis with packages that combine blanket support and price reduction measures, our results help clarify how such relief measures should be designed (e.g., Varga et al. 2022). The distributional effectiveness and efficiency of subsidies, energy tax credits, or targeted transfers depends on which households consume the subsidized goods and how they adapt to changes in prices. Classical fiscal results suggest that redistribution can be achieved through a system of taxes and transfers if price adjustments are similar across the income distribution. Different responses may warrant product-specific interventions, such as targeted transfers or price ceilings. In our setting, we report this difference by estimating income-dependent adjustment responses.
Who bears the brunt of an energy price shock depends not only on who is most affected, but also on who is able to adapt. Low-income households are doubly vulnerable because they spend more of their budget on energy but also have less ability to reduce their electricity use. Although the labor income of those who are working has increased, we do not see any entry into the labor force of those whose income comes primarily from government benefits or pensions. These represent targeted relief rather than broad subsidies.
The results also suggest that compensating low-income households through subsidized prices need not incur large efficiency costs. In our setting, these households reduced their electricity use very little as prices increased. This suggests that the efficiency costs of targeted price support for low-income households may be lower than often feared.
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