MONETARY POLICY REPORT | WINTER 2022 (box 2)
(author: Ondřej Michálek)
Both the global and Czech economies are now experiencing a surge in energy commodity prices. Identifying the duration of its effect and the size of its pass-through to domestic consumer prices is vital for estimating inflation pressures and setting monetary policy appropriately. It is also crucial for central banks to determine how the current dramatic rise in energy prices will affect consumer demand. The recovery in consumer demand could be quite fragile if the epidemic situation worsens again, consumer sentiment turns volatile, and the outlook for households’ financial situation becomes uncertain.
Housing-related energy costs form a large part of household expenditure. Moreover, heat, light and energy have practically no substitutes. The effect of the high energy price growth on household consumption was already incorporated into last year’s autumn forecast. This box analyses these relations in more depth and complements them with an explicit estimate of the size of the effect.
Price elasticities are key to quantifying the impact of high energy prices on household consumption.[1] The analysis in this box uses individual annual data from the CZSO’s household budget statistics, which include total expenditure on individual consumer items broken down by kind (CZ-COICOP) at the household level. These items are assigned average unit prices in the given year based on the consumer basket used by the CZSO to measure inflation. For each item, the quantity purchased across all households is then calculated. The analysis draws on a sample of data for 2017–2020. The final data set contains a panel of more than 3,500 observations in the period under review.
Before their elasticities are empirically estimated, the consumer items for each household are aggregated into eight main categories (see Chart 1). Given the different mixes of items consumed, each household faces different prices for the individual aggregated categories. This is a necessary condition for calculating elasticities using the chosen method. A typical Czech household spends the highest amount – around a quarter of its budget – on food. Spending on energy accounts for slightly more than a tenth of its budget.
The price elasticity of demand indicates how a 1% change in the price of good/goods category X affects demand for that good/category. If the elasticity is less than ‑1, demand is said to be price elastic: a 1% increase in price leads to the quantity demanded dropping by more than 1%. An infinitely negative elasticity means that demand is perfectly elastic. Conversely, a good is price inelastic if the elasticity is between ‑1 and 0. A perfectly price inelastic good is one with an elasticity of zero: the quantity demanded does not change no matter how much the price moves. The price elasticity may theoretically be even higher than 0 if the quantity demanded increases when the price of the good goes up (Giffen’s paradox).
The cross price elasticity of demand indicates how a 1% change in the price of good/goods category X affects the quantity of good/category Y demanded. If this elasticity is positive, the two goods are substitutes and growth in the price of X causes growth in the quantity of Y demanded. In the opposite case (i.e. if the cross price elasticity is negative), the relationship between the two goods is complementary.
The income elasticity of demand indicates how a 1% change in a consumer’s income affects the quantity of good/goods category X demanded. If this elasticity is negative, X is an inferior good. An elasticity of between 0 and 1 indicates a normal (non-essential) good. If the income elasticity is higher than 1, X is considered to be a normal (luxury) good.
Chart 1 – The structure of consumption expenditure has been almost constant in recent years
shares of categories in total consumer expenditure in %
Looking at the price elasticities[2] (see Table 1), it is apparent that the estimated levels are statistically significant for all the categories, and all the categories are price inelastic (i.e. they have a negative elasticity of greater than ‑1) to varying degrees. The drop in the quantity demanded given a price increase of 1% is lowest in the cases of food (‑0.65), energy (‑0.75) and housing (‑0.75), i.e. items that no household can do without. At the opposite end are health and personal care and education and leisure, i.e. largely non-essential categories.
Table 1 – Demand for food, energy and housing is the least price elastic, while demand for clothing and footwear falls the most if energy prices go up
price elasticity and cross price elasticity; the figures in the table show the impact of a 1% increase in price in the categories in the columns on the quantity demanded in the categories in the rows; * denotes statistical significance of elasticity at the 5% level; the more negative the elasticity, the darker the shade
Turning to the cross elasticities, almost all the categories of goods turn out to be complements of the energy category, i.e. the cross price elasticities are negative. The effect of a fall in the quantity demanded due to higher energy prices is strongest in the categories of clothing and shoes (‑0.17) and housing (‑0.15). The drop in consumption caused by growth in energy prices is weaker but still significant in transport and communication and furniture and electronics. Unlike housing, all these categories can be viewed as less essential than energy. In other words, households will prefer to save on items they can do without than to further reduce their consumption of light, heat and so on.
To estimate the current impact of the high energy prices on household consumption, a shock energy price increase of 20%, which is broadly in line with the current forecast for this year, was applied in the model simulation. However, the resulting growth in the price of the entire energy category is slightly smaller, as the 20% price increase is assumed “only” for electricity, gas and heat, which account for around 95% of this category.[3] In line with the estimated cross elasticities, the largest drop in expenditure is seen in the categories of clothing and shoes, housing[4] and transport and communication (see Table 2). By contrast, household expenditure on energy rises by more than 3%, even though energy consumption falls by almost 14%. The total impact of the energy price increase considered on household consumption can be derived as the sum of the changes in the quantity consumed weighted by the shares of the individual categories after the change in price. A 20% increase in electricity, gas and heat prices leads to a decrease in real household consumption of almost 2.5% in whole-year terms.
Table 2 – Besides cutting down on energy consumption, households respond to growth in energy prices mainly by reducing demand for housing, transport and communication, and clothing and shoes
simulation of 20% increase in electricity, gas and heat prices; % and pp
| Share of expenditure | Change in | Impact on real household consumption in pp | |||
|---|---|---|---|---|---|
| before price change | after price change | expenditure | quantity | ||
| Energy | 13,9 | 14,3 | 3,3 | -13,9 | -2,0 |
| Clothing & Shoes | 4,1 | 4,0 | -2,2 | -2,2 | -0,1 |
| Education & Leisure | 19,1 | 19,0 | -0,1 | -0,1 | 0,0 |
| Food | 28,0 | 28,1 | 0,2 | 0,2 | 0,1 |
| Furniture & Electronics | 6,0 | 5,9 | -0,7 | -0,7 | 0,0 |
| Health & Personal Care | 6,6 | 6,6 | -0,3 | -0,3 | 0,0 |
| Housing | 11,6 | 11,4 | -2,0 | -2,0 | -0,2 |
| Transport & Communication | 10,8 | 10,7 | -1,0 | -1,0 | -0,1 |
| Overall impact on real household consumption in % (figures may not add up owing to rounding) | -2,4 | ||||
Note: The change in expenditure is calculated as the share of expenditure after and before the price change. The change in quantity differs from the change in expenditure only in the energy category, as the price changes in this category only. This column is equal to the second column divided by the first one multiplied by the old price divided by the new one. The impact on consumption is calculated as the change in quantity multiplied by the share of expenditure after the price change.
The surge in housing-related energy prices will thus have a significant impact on real household consumption this year. This analysis shows that a 20% increase in electricity, gas and heat prices implies a negative whole-year impact on real household consumption of almost 2.5%. This effect is partially offset by spending of forced savings created during the previous shutdowns of retail and services. On the other hand, there may also be non-linear and second-round effects, which are difficult to capture using the linear model applied. According to PAQ Research, the absolute growth in housing expenditure will be similar across all households. Low-income households will thus be hardest hit. The share of housing costs in their total expenditure will rise from 55% to 63%.[5] The change in household consumption will also depend on how much firms will be able to incorporate the growth in their costs caused by higher energy commodity prices into their end prices. If they succeed only partially, this could be reflected in a drop in demand for labour, which would in turn reduce household consumption further. However, this scenario seems unlikely.
[1] The description of elasticities is based on the textbook Principles of Microeconomics 8th Edition (Mankiw, G., 2018).
[2] The theoretical starting point for estimating the elasticities is the QUAIDS (Quadratic Almost Ideal Demand System) model. It allows us to determine the optimum allocation of expenditure even at a high level of goods aggregation. The econometric model is estimated using the SURE (Seemingly Unrelated Regressions) method, which allows us to estimate several regression equations simultaneously. A detailed description and derivation of the QUAIDS model is available in CNB WP 8/2010: Effects of price shocks to consumer demand. Estimating the QUAIDS demand system on Czech household budget survey data (Dybczak, Tóth, Voňka, 2010). The analysis draws on Measuring the efficiency of VAT reforms: A demand system simulation approach (Tóth, Cupák, Rizov, 2021).
[3] This implies that the prices of the other items in the consolidated energy category remain constant.
[4] Rent, imputed rent and the cost of purchases of material and services related to housing and maintenance of the house.
[5] For details, see https://www.paqresearch.cz/post/pr%C5%AFm%C4%9Brn%C3%A1-dom%C3%A1cnost-si-za-energie-p%C5%99iplat%C3%AD-940-k%C4%8D-pomoci-m%C5%AF%C5%BEe-odstropov%C3%A1n%C3%AD-p%C5%99%C3%ADsp%C4%9Bvku-na-bydlen%C3%AD (available in Czech only).