Energy prices and private consumption: what are the channels?

Prepared by Niccolò Battistini, Virginia Di Nino, Maarten Dossche and Aleksandra Kolndrekaj

Published as part of the ECB Economic Bulletin, Issue 3/2022.

1 Introduction

The recent increase in energy prices raises the question of the extent to which households will reduce their consumption in response. With the global economy in the process of recovering from the coronavirus (COVID-19) pandemic, the prices of many commodities – including oil and gas – have soared over the last year or so. Since demand for energy is inelastic in the short run, those large price increases imply significant declines in households’ purchasing power, which will need to be absorbed through (i) reduced consumption of non-energy goods and services, (ii) a reduction in savings or (iii) an increase in income. This article assesses the extent to which those three margins are playing a role in the transmission of higher energy prices to aggregate consumption. In addition, it analyses the distributional impact of higher energy prices, as the effect on individual households tends to vary considerably. Since the distributional impact of such price rises has the potential to be very significant, that may warrant a separate policy response independently of the macroeconomic implications of those developments.

The rise in energy prices should be seen in the context of an exceptional economic recovery, but other factors are also playing a role. While the impact that energy prices have on consumption has been studied before, the recovery following the COVID-19 crisis is atypical from a historical perspective. Thus far, it has been characterised by a surge in global demand for durable and non-durable consumer goods, leading to unprecedented bottlenecks in production and trade, with households having accumulated record levels of savings in the course of the pandemic.^[1] Moreover, the supply of energy has been hampered by a lag in the production of oil, as well as geopolitical tensions – especially Russia’s recent invasion of Ukraine – and technical disruptions affecting the provision of natural gas to European countries.^[2] It is important to account for these confounding factors in order to understand the aggregate impact that higher energy prices will have on private consumption and formulate an appropriate policy response.

This article presents new evidence for the euro area and is structured as follows. Section 2 outlines relevant existing literature. Section 3 presents new empirical evidence from both an aggregate and a disaggregated perspective. The aggregate perspective focuses on identifying the source of energy price fluctuation, while the disaggregated perspective focuses on distributional implications beyond the aggregate impact. Importantly, in order to provide a timely assessment of the macroeconomic and distributional implications of large changes in energy prices, the aggregate and disaggregated analyses are both based on survey data. Section 4 concludes and identifies a number of policy implications.

2 Existing literature

When countries are net importers of energy, higher energy prices generally entail a worsening of their terms of trade. Backus and Crucini showed, using a set of industrialised countries, that a large percentage of the variability of terms of trade is associated with extreme movements in oil prices.^[3] They studied the terms of trade and their correlation with other variables in a setting in which events affecting the production of oil interacted with the production and sale of other goods. De Michelis et al. found that oil price increases generally drive a wedge between consumption developments in oil-importing and oil-exporting countries.^[4] Higher oil prices transfer wealth from oil importers to oil exporters, and that wealth effect, in turn, has a negative impact on consumption in oil-importing countries through multiplier effects. It is worth noting that this impact may be larger in sectors which produce goods that are complementary to the consumption of oil, such as the automobile sector.

Higher energy prices do not always lead to a contraction in consumption; indeed, they can also be a consequence of increased consumption. Kilian, for example, showed that changes in the price of oil can reflect both oil supply shocks and shocks to global demand.^[5] The economic impact of an oil price change which is caused by an unanticipated aggregate global demand shock will be very different from that of an oil price rise which is caused by an unanticipated shortfall in the production of oil. Hence, it is important to understand the extent to which increases in the price of oil are driven by different kinds of shock before formulating policy responses. Bodenstein et al. argued that the source of an oil shock matters greatly for the optimal monetary policy response to fluctuations in energy prices.^[6] They looked at a wide range of monetary policy rules and identified an easily implementable welfare-maximising rule whereby the central bank puts zero weight on the price of oil, but responds to wage inflation. In the wake of fluctuations in oil prices, stabilising wage inflation fosters the stabilisation of core inflation, in line with earlier findings by Aoki.^[7] When oil prices rise as a result of an increase in aggregate demand, wages also rise, and monetary policy will need to become tighter. Conversely, if oil prices increase as a result of disruptions in oil supply, and there are no second-round effects on wages, monetary policy does not need to tighten in order to stabilise core inflation.

Large increases in energy prices can affect individual households in very different ways. For example, Michael and Hagemann showed that exposure to higher energy inflation differs widely across individual households in the United States.^[8] Because they spend a relatively large percentage of their income on energy, poor households are particularly hard hit in terms of inflation when energy prices surge. Hobijn and Lagakos confirmed those earlier findings, but also found that households which face higher than average inflation in one year (owing to higher energy prices) are not very likely to be confronted with the same inflation disparity the following year.^[9] This implies that poorer households do not, over time, systematically face higher inflation as a result of their higher relative expenditure on energy. At the same time, it suggests that, in the case of a large energy price shock, the adverse impact on some households may be so large that it easily outweighs any positive impact seen through macroeconomic channels (e.g. employment).

3 Empirical evidence from the euro area

Aggregate perspective

Energy prices affect private consumption through both direct and indirect channels. An increase in energy prices directly affects households’ purchasing power through higher prices for energy products (electricity, gas, petrol, heating oil, etc.). In the euro area, about 30% of all energy use takes the form of final consumption – i.e. the use of such products by consumers (Chart 1). The remainder involves energy being used in the production of non-energy goods and services (i.e. intermediate consumption). A rise in energy prices entails an increase in the production costs of non‑energy sectors and – to the extent that producers of non‑energy goods and services adjust their final prices – a further direct reduction in households’ purchasing power. If those costs cannot be passed on to the final prices of the relevant goods, there will be an indirect impact on households’ purchasing power, since producers in the relevant sectors will either cut wages or have lower profits to distribute. Moreover, in advanced economies that are large producers of energy (e.g. Canada, Norway, the United Kingdom and the United States), indirect effects through the wages and profits of energy producers are also important.

Chart 1

Energy use and prices in the euro area

(left-hand scale: EUR billions; right-hand scale: index, 2015=100)

The impact of energy price changes on real disposable income can be proxied by the ratio of the GDP deflator to the private consumption deflator. For net importers of energy (such as the euro area), energy prices exhibit a stable negative correlation with the terms of trade, interpreted as the amount of imported goods that an economy can purchase per unit of exported goods. When assessing the impact that energy price changes have on consumption, a key proxy is the ratio of the GDP deflator to the private consumption deflator (or that of the income deflator to the spending deflator).^[10] In the euro area, (real) energy prices are negatively correlated with that ratio (Chart 2). That measure is well‑founded from a theoretical perspective and captures both direct and indirect channels through which energy prices affect households’ real disposable income.^[11] Even if the channels through which energy prices affect the economy change, this approach still shows stability in the relationship between energy-induced changes in purchasing power and private consumption. This is relevant in the face of changes to the energy intensity of consumption and innovations in the production of energy and non-energy goods.

Chart 2

Energy prices and the terms of trade

(index, 2010 average=100)

Well-known episodes involving large swings in energy prices highlight the role of different transmission channels. Chart 3 breaks the dynamics of households’ real disposable income down into various sources of income derived from economic activity (wages, profits and other property income), net transfers from the government, and the terms of trade (proxied by the ratio of the GDP deflator to the private consumption deflator). Fluctuations in the terms of trade stemming from large changes in the supply of energy appear to have been an important driver of household income after (i) OPEC increased oil production, leading to a collapse in energy prices in the first quarter of 1986, and (ii) Iraq invaded Kuwait, leading to soaring energy prices in the third quarter of 1990. In contrast, developments in aggregate economic activity appear to have been the main channel for the drop in household income in the fourth quarter of 2008 following Lehman Brothers’ default, amid falling energy prices and ensuing gains in the terms of trade. In the early stages of the COVID-19 pandemic, the abrupt fluctuations in economic activity were the main transmission mechanism, whereas the terms of trade weighed on household income at the end of 2021. However, in order to identify the underlying drivers, we need to use indicators with greater timeliness and frequency, such as survey data.

Chart 3

Households’ real disposable income and consumption

(annual percentage changes and percentage point contributions)

Household surveys provide timely and frequent information on inflation and private consumption, as well as their underlying drivers. Historically, the index indicating households’ plans to make major purchases in the next 12 months that is derived from the European Commission’s consumer survey has tracked year‑on‑year growth in real private consumption of durable goods reasonably well, although the correlation between the two declined substantially during the first wave of the pandemic (Chart 4). Moreover, that survey-based indicator of households’ consumption expectations exhibits good leading properties with regard to actual future consumption.^[12] Indeed, surveys contain information that may help with the timely identification of underlying drivers of households’ consumption decisions (Box 1). Increases in expected inflation can be driven by various factors, and some factors can potentially have opposite effects to others in terms of households’ spending plans. In the context of strengthening economic activity with higher levels of “demand-pull” inflation, consumption may rise as real income increases. However, in the presence of weakening economic activity with higher levels of “cost-push” inflation, consumption may fall instead as real income declines.

Chart 4

Fluctuations in consumption over time

(left-hand scale: standardised index, long-run average=0; right-hand scale: annual percentage changes)

Thus far, the recovery in consumption has been driven primarily by demand tailwinds, but cost-push headwinds are increasingly clouding the near-term outlook. In the early stages of the pandemic, as their financial prospects deteriorated, households scaled back their consumption and saving plans, mainly in response to contractionary cost-push shocks and, soon afterwards, demand-pull shocks (Chart 5).^[13] Since early 2021, strong demand-pull shocks have contributed to recoveries in households’ expected financial conditions, consumption and savings. However, the rise in commodity prices that has been observed since the summer of 2021 has increasingly been regarded as stifling households’ expected financial situation, thus weighing on their spending plans. In March 2022, supply‑side contractionary forces – exacerbated by the ongoing geopolitical tensions – more than offset demand-side expansionary factors driving consumption plans.

Chart 5

Demand-pull and cost-push drivers of the expected consumption, financial situation and savings of households

(contributions to standard deviations from long-term averages)

Box 1
Disentangling demand-pull and cost-push forces: does it matter for consumption?

Prepared by Niccolò Battistini and Maarten Dossche

This box uses an empirical time series model to assess the role that households’ perceptions of the economy play in determining their plans to make major purchases. The European Commission’s consumer survey measures households’ expectations about economic activity and inflation, as well as their own spending plans, financial situation and savings. A structural multivariate (vector autoregression) model has been estimated using survey data for the period from January 1985 to February 2022. In order to disentangle the various structural drivers, the model assumes that expected economic activity improves after a perceived demand-pull shock and declines after a cost‑push shock, while both shocks lead to higher inflation expectations. The goal of this box is to look at the ways in which households’ expected consumption, financial situation and savings react to such shocks. Consequently, the responses of those three variables are left unrestricted.^[14]

The responses to demand-pull and cost-push shocks suggest that the sources of such shocks matter for households’ expected consumption, financial situation and savings (Chart A). In order to compare the magnitude of the responses to the various shocks, each shock is standardised so as to entail the same impact (i.e. 1 standard deviation) on expected inflation. Hence, the standardised demand-pull and cost-push shocks induce observationally equivalent inflation pressures, but their economic impact is strongly asymmetrical. In line with theoretical predictions, households’ expected consumption, financial situation and savings improve significantly after a perceived demand-pull shock and deteriorate after a perceived cost-push shock. Moreover, confirming typical identifying assumptions in empirical literature, the results show that cost-push shocks have a more persistent impact on households’ expected consumption, financial situation and savings over the following two years relative to demand-pull shocks. Finally, looking at the horizon as a whole, households’ expectations appear to react more strongly to cost-push shocks than demand-pull shocks.^[15]

Chart A

Responses to demand-pull and cost-push shocks

(x-axis: months; y-axis: standard deviations)

Analysis of the drivers of household inflation expectations around the time of well-known historical episodes validates the choice of identifying assumptions (Chart B). For instance, the model is good at capturing the cost-push nature of the decline in expected inflation that resulted from the increase in OPEC oil production and the ensuing collapse in oil prices in the first few months of 1986. Cost‑push forces also explain most of the surge in consumer price expectations that was triggered by the bout of oil price inflation which followed Iraq’s invasion of Kuwait in the summer of 1990. Moreover, the model correctly depicts the demand-driven drop in expected inflation following Lehman Brothers’ default in the second half of 2008 at the start of the global financial crisis. Overall, the model appears to accurately depict changes in consumer price expectations in response to both demand‑pull and cost-push forces.

Chart B

Contributions of demand-pull and cost-push forces during key episodes

(left-hand scale: contributions to standard deviations from long-term averages; right-hand scale: annual percentage changes)

Expected inflation

Expected consumption

Looking at expected consumption during those same episodes, cost-push forces led households to step up their consumption plans during the OPEC-induced collapse in the first few months of 1986 and abruptly downsize them in the wake of Iraq’s invasion of Kuwait in the summer of 1990. In contrast, following Lehman Brothers’ default in the second half of 2008, the persistent downward pressure that was exerted on expected consumption stemmed mainly from demand-pull forces. Overall, cost-push forces appear to be the main drivers in episodes originating from the energy sector (especially the oil market).

Disaggregated perspective

While a change in energy prices can have several origins, an individual household will tend to perceive it as an exogenous shock to its real disposable income. When making decisions on consumption and savings, households take energy prices as a given, not considering the implications that their decisions have for energy prices. When energy prices rise, it leads to a reduction in households’ real disposable income, even if that price rise is caused by increased demand for energy. Depending on the aggregate economic conditions, a rise in energy prices will either exacerbate any decline in disposable income or partly offset any increase (e.g. in the context of an economic upturn). For those reasons, this section focuses on the direct distributional effects of changes in energy prices, while controlling for the underlying macroeconomic drivers of energy shocks, which were explored above in the section on the aggregate perspective.

Energy is a necessary consumer good, so household exposure to fluctuating energy prices declines as income rises. Since energy consumption responds to basic needs, which households cannot give up entirely, demand for energy tends to be price inelastic in the short run. Households typically accommodate any rise in energy prices by revising their saving plans and reallocating spending. However, the extent to which households need to resort to either of those strategies depends on their exposure to energy repricing. The share of households’ monthly income that goes on utilities and transport services (i.e. energy-intensive consumption) is an approximate indicator of their exposure to an energy price change. That exposure differs widely across income groups, standing at almost 35% for the lowest quintile of the income distribution but less than 10% for the top quintile.^[16] Thus, the distributional effects of a rise in energy prices are sizeable, with low-income households facing almost four times the impact that is experienced by households in the top quintile of the income distribution (Chart 6).^[17]

When spending on energy rises, households reduce their purchases of essential goods and services to a small extent. The average elasticity of substitution between spending on energy and other essentials (e.g. groceries, housing and health services) is fairly low, albeit the response varies across income quintiles (Chart 7; see Box 2 for details of the estimation methodology). Where basic needs are met primarily through low-cost items (which is the case for the households with the lowest incomes), there is very limited scope to compress spending on other essentials in response to rising energy prices (with that scope estimated at 0.2 percentage points of total spending for each percentage point rise in energy spending).^[18]

Chart 6

The exposure of households to energy price shocks

(x-axis: income quintiles; y-axis: percentages)

Higher-income households make fewer adjustments to their spending on essentials, as energy-sensitive spending accounts for a smaller percentage of their income. For the same absolute increase in energy spending, households in the top quintile of the income distribution reduce their spending on essentials by just 0.15 percentage points. Middle-income households tend to react more, being more likely to replace branded products with lower-cost alternatives.^[19] Within income quintiles, liquidity‑constrained households (i.e. those whose net income is insufficient to cover total spending and debt repayments) tend to cut their consumption of essentials somewhat more than those that have a liquidity buffer for unexpected expenses.

Chart 7

Changes in spending on essentials when energy spending rises

(x-axis: income quintiles; y-axis: percentage points of total monthly spending)

Chart 8

Changes in savings in response to a rise in energy spending

(x-axis: income quintiles; y-axis: percentage points of income)

Households draw on their savings to cushion the impact that higher energy prices have on consumption. Empirical evidence confirms that – in the short run, at least – households substantially reduce their saving ratios in order to accommodate increased spending on energy (albeit to a lesser extent if liquidity buffers for unexpected expenditure are limited).^[20] Identifying the responses of savings across different income quintiles reveals that, for the same absolute increase in energy spending, the reduction in savings is inversely correlated with the family’s income and about five or six times greater for households in the lowest quintile of the income distribution relative to those in the top quintile (Chart 8).

Box 2
Estimating household responses to changes in energy spending

Prepared by Virginia Di Nino and Aleksandra Kolndrekaj

This box presents details of the econometric methodology which has been used to study the effect that changes in monthly energy spending have on households’ saving ratios and spending on essentials. That analysis, which uses microdata from the ECB’s Consumer Expectations Survey, covers the six largest economies in the euro area, with more than 75,000 observations over the period since April 2020. Each quarter, the CES collects information about households’ monthly spending in 12 major areas (including utilities, transport services, food, health and housing services). Saving flows are derived by subtracting total monthly spending from monthly net income. “Essential” spending refers to food, beverages and tobacco, health and housing services.

Two linear panel models looking at quarterly changes in the monthly saving ratio and spending on essentials as a share of total spending yj,c,t-yj,c,t-3are specified as a function of the quarterly change in the percentage of income that is spent on utilities (xj,c,t-xj,c,t-3):

That equation includes the monthly saving ratio of three months earlier sj,c,t-3, which captures the impact of major one-off purchases in the previous period that have repercussions for the saving ratio.

This analysis faces a number of challenges. Households may find it difficult to accurately recall all of their spending, broken down by category, so they may potentially misreport their total spending. The use of first differences in the specification partly controls for these issues, eliminating any household-specific constant biases in the data. The specification also includes several fixed effects with the aim of identifying the key parameter β, which measures the reaction to a change in spending on utilities, controlling for several confounding effects. Those fixed effects relate to (i) households’ heterogeneous characteristics (α_j), such as the size and location of inhabited dwellings, and the composition of families, (ii) country-specific but time-varying factors (α_c,t), such as the differing economic conditions that characterise individual countries (GDP growth, inflation rates, etc.), and (iii) factors that vary across income groups and over time (α_i,t), which can influence decisions on savings and spending, such as government measures mitigating the pandemic’s impact on households.

Households with greater exposure to energy prices view measures aimed at easing the burden of rising energy prices as less adequate. Government intervention is primarily aimed at mitigating the unequal impact that rising energy prices have across households, supporting poorer households (who tend to spend more on energy as a share of their income). Despite benefiting most from them, households with very high exposure to energy prices tend to take the view that those policies are not sufficient to compensate for the negative impact of energy price spikes (Chart 9).

Chart 9

Perceived adequacy of government interventions and energy exposure

(x-axis: spending on utilities as a percentage of total income; y-axis: perceived adequacy of intervention on a scale of 0 to 10)

4 Conclusions

The recent rise in energy prices is a clear headwind for the recovery in consumption. In the early stages of the pandemic, as their financial prospects deteriorated, households scaled back their consumption plans, mainly in response to contractionary cost-push shocks and, soon afterwards, a series of negative demand‑pull shocks. Since early 2021, positive demand shocks have led to a recovery in households’ expected financial conditions, consumption and savings. However, the rise in commodity prices that has been observed since the summer of 2021 has increasingly been regarded as stifling households’ expected financial situation, thus weighing on their spending plans.

Increases in energy prices have significant distributional implications, which call for targeted fiscal policy measures. The impact that energy prices have on household income and spending depends primarily on the household’s level of exposure. Low‑income households with high levels of exposure tend to experience considerable financial distress when energy spending rises unexpectedly, and they respond to such shocks by reducing savings or delaying payments. As a result, those households are more likely to feel that there is a need for governments to mitigate the adverse impact of higher energy prices.