Inflation in the eastern euro area: reasons and risks

10 January 2024
By Matteo Falagiarda

Within the euro area, countries in central and eastern Europe have recently experienced the highest inflation rates. But why, exactly? The ECB Blog looks at the reasons for these higher prices and highlights the resulting risks and vulnerabilities.

Since 2021 inflation in euro area countries in central and eastern Europe (EACEE) has significantly outpaced that of the euro area as a whole.[1] The differentials have narrowed in recent months but remain high for core inflation, which excludes energy and food prices (Chart 1). If large cumulated inflation differentials persist in a monetary union like the euro area, they can lead to competitiveness losses. This, in turn, could stoke country-specific macroeconomic vulnerabilities, such as deteriorating current accounts, higher external debt, downward demand pressures and rising unemployment. So understanding the sources of high inflation is important to deal with the associated risks.

Chart 1
Inflation differentials in EACEE countries vis-à-vis the euro area average

(percentage points)

Sources: Eurostat and author’s calculations.
Notes: Averages across EACEE countries are unweighted averages. Core inflation refers to HICP excluding energy and food. The latest observations are for November 2023.

Strong impact of global shocks
Part of the reason for the relatively high initial inflation in EACEE countries is their vulnerability to recent adverse global shocks: disruptions in global supply chains, supply-demand imbalances after the COVID-19 pandemic as well as the ramifications of the Russian invasion of Ukraine. These shocks hit all European economies. But their impact was stronger in EACEE countries, in part due to certain structural features of these economies (Chart 2).
First, EACEE countries typically display a higher energy intensity of production than the euro area average, mainly owing to larger energy-intensive sectors (i.e. manufacturing and transport) and fewer energy-efficient appliances and buildings. Second, the share of energy and food in their consumption baskets is higher than the euro area average, which we often see in economies with lower average incomes. Third, most of these economies depended heavily on Russian energy prior to the outbreak of the war, making them more vulnerable to energy supply disruptions. Fourth, these countries are deeply integrated in global value chains (GVC), implying a larger impact of global supply bottlenecks.[2]

Chart 2
Higher vulnerability of EACEE countries to recent global shocks

(left panel: kilogrammes of oil equivalent per thousand euro in PPS; middle and right panels: percentages)

Sources: Eurostat, OECD (TiVA) and author’s calculations.
Notes: Averages across EACEE countries are unweighted averages. Euro area figures for energy intensity and import dependency are calculated using country-weights based on nominal GDP. Energy intensity measures the energy needs of an economy and is calculated as units of energy per unit of GDP. Data on energy intensity refer to 2021. Russian oil refers to Russian oil and petroleum products. Russian gas refers to Russian natural gas. Data on import dependency on Russian oil and gas refer to 2020. Backward GVC participation is the foreign value added embedded in domestic exports. Data on backward GVC participation refer to 2020. Data on weights in the HICP basket refer to 2022.

Persistent domestic price pressures
While external shocks were an important driver of initial inflation differentials, domestic factors also play a prominent role (Chart 3). How much pipeline pressures (those emerging at the early stages of the production and distribution chain) ultimately pass through to consumer goods partly depends on how much firms absorb them by reducing profit margins. While euro area firms have recently expanded unit profits, recouping past real profit losses and building buffers amidst high uncertainty, the unit profit increase was larger in the EACEE region. This has an effect on domestic price pressures. The larger increase in unit profits in EACEE countries possibly reflects the stronger pipeline pressures, the more pronounced impact of global supply bottlenecks, or a lower degree of competition among firms, especially in the smaller countries of the region.

Domestic factors have played an increasingly prominent role in supporting inflation.

Labour market conditions have also remained tight in all EACEE countries, with historically low unemployment rates and persistent labour shortages resulting in robust wage growth in excess of productivity growth. This exerted upward pressure on inflation, albeit with limited risk of a price-wage spiral. Shortages in labour supply are apparent from less favourable developments in the labour force and working age population in these countries compared to the euro area overall. These trends are due to migration outflows of highly skilled young people and a rapid population ageing.
Stronger domestic price pressures in EACEE countries may have also reflected that higher inflation temporarily reduced real interest rates. As the pick-up in inflation started earlier and was stronger than in the rest of the euro area, borrowers in these countries have temporarily experienced a decline in the real value of their outstanding debt. In addition, to the extent that a continuation of relatively high inflation has been expected, ex-ante real financing costs could have been relatively low. Both factors, combined with resilient labour markets, may have contributed to stronger (albeit now moderating) domestic demand and credit dynamics.[3]

Chart 3
Selected indicators on domestic factors

(percentage changes from Q4 2019 to Q3 2023; unemployment rate: average percentages over the period January 2020 – September 2023)

Sources: Eurostat, ECB and author’s calculations.
Notes: Averages across EACEE countries are unweighted averages. Unit labour costs are defined as compensation per employee divided by labour productivity. Unit profits are defined as gross operating surplus divided by real GDP. Loans to firms and households are notional stocks adjusted for sales and securitisation. Labour force is the active population between 15 and 64. Working-age population refers to the number of persons aged between 15 and 64.

Analysis confirms that the bulk of the initial increase in inflation in EACEE countries reflected global external shocks (Chart 4). The estimates indicate that external shocks played a strong role in boosting inflation above the euro area aggregate. At the same time, the model shows that domestic price pressures have increasingly contributed to the widening of inflation differentials vis-à-vis the euro area. While external sources of inflation eased since the end of 2022, domestic factors are estimated to have continued to exert significant upward pressures on inflation in the most recent period as well.

Chart 4
Decomposition of headline inflation

(left-hand and middle panels: cumulated percentage point contributions to headline inflation since December 2019; right-hand panel: cumulated contributions to changes in the headline HICP index from December 2019 to September 2023)

Sources: Author’s calculations.
Notes: The left-hand and middle panels show the cumulated percentage point contribution of different types of shocks to explain the evolution in headline inflation since December 2019. The right-hand panel shows the cumulated contribution of different types of shocks to explain the evolution in the headline HICP index since December 2019. Global factors include an energy price shock and a global supply bottlenecks shock; other factors include a domestic supply shock, a monetary policy shock and an unidentified shock. The contributions are estimated in a Bayesian vector autoregressive model. More details on the model can be obtained upon request from the author.

Conclusions
The recent drop in energy prices and the unwinding of global supply bottlenecks have already begun to narrow headline inflation differentials of EACEE countries vis-à-vis the euro area. However, domestic price pressures, in part resulting from a stronger pass-through of external shocks amidst tight labour markets, are keeping underlying inflation in these countries persistently higher than the euro area average. At the same time, high cumulated inflation increased the relative price level, eroding price competitiveness, as reflected by the strong appreciation of the real effective exchange rates, implying that these countries might be confronted with rising external vulnerabilities and the related consequences.
These developments point to the need for policy action. As the single monetary policy cannot address such country specific developments, national fiscal and structural policies are best suited to mitigating potential risks. The precise policy response will depend on country-specific features. In the near term, a tighter fiscal policy stance could help to dampen inflationary pressures stemming from domestic demand. In addition, structural policies could support the competitiveness of these economies, their potential growth and resilience to future shocks, for example by fostering investment in innovation and human capital as well as strengthening adjustment flexibility.
The views expressed in each blog entry are those of the author(s) and do not necessarily represent the views of the European Central Bank and the Eurosystem.
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The EACEE countries in this blog post comprise Estonia (EE), Latvia (LV), Lithuania (LT), Slovakia (SK), Slovenia (SI) and Croatia (HR). Notice that during the inflation surge in 2021-2022, Croatia had not yet adopted the euro. While EACEE economies all have their country-specific features, there are also some common characteristics. They are all small open economies that adopted the euro during the past 15 years. While highly integrated with the rest of the euro area, these countries were also potentially more exposed to the shocks stemming from the Russian invasion of Ukraine given their geographical proximity. In the last two decades, they have been undertaking a process of gradual convergence, but their income per capita still lags that of the euro area average. An adverse demographic outlook and subdued productivity growth represent an obstacle for a fast catching-up of these countries. On the positive side, these countries typically display relatively low public and private debt levels compared with other euro area countries.
Moreover, in the Baltics changes in commodity prices tend to transmit quickly to consumer prices on account of particularly flexible price setting.
In some EACEE countries, the ample liquidity in the banking sector has also temporarily limited the transmission of tighter ECB’s monetary policy.

 
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New experimental statistics on distribution of household wealth in euro area provide quarterly information to policy makers, in line with national accounts
First new data show that household net wealth in euro area increased by 29% over last five years, with homeowners’ net wealth increasing more than that of non-homeowners
Inequality, as measured for example by share of wealth held by top 5% versus bottom 50%, decreased slightly over past five years

The European Central Bank (ECB) has today published experimental statistics on Distributional Wealth Accounts (DWA) to provide quarterly and timely household distributional information that is consistent with the national accounts. The new data have been developed to support the ECB’s 2021 monetary policy strategy, which aims to include a systematic assessment of the two-way interaction between income and wealth distributions and monetary policy[1]. The release also follows recommendations of the G20 Data Gaps Initiative[2].
The DWA link household-level information from the Household Finance and Consumption Survey (HFCS) to macroeconomic information available in the sector accounts and therefore complement existing household survey data. The data will be compiled every quarter and published five months after the end of each period.
The DWA provide data on net wealth, total assets and liabilities[3] and their components. Households are broken down into the top five deciles of net wealth and the bottom 50% as well as by employment and housing status.
Through these data, it is possible to analyse the effects of, for example, growing housing wealth and the rising value of listed shares on the distribution of household wealth. The DWA results show that the increase in housing wealth in recent years has been more equally distributed than the increase in the value of listed shares (Chart 1).

Chart 1: Housing wealth (left) and listed shares (right), by net wealth decile, euro area

The significant rise in euro area household net wealth observed in national accounts over the past five years (29% or about €13.7 trillion) was accompanied by a slight decrease in inequality, partly because homeowners, who account for more than 60% of the population, benefited from increased housing prices. Their net wealth (per household) increased by 27% over this period. In parallel, the net wealth of non-homeowners, making up 40% of the population, grew by 17%, mainly owing to the rise in deposits observed over this period.
The DWA dataset also includes the Gini coefficient for net wealth, data on median and mean net wealth, the share of net wealth held by the bottom 50%, the top 5% and the top five deciles of households, as well as the debt-to-asset ratio by household net wealth deciles.
The DWA results show that, in the euro area, the share of net wealth held by the top 5% of households of the net wealth distribution dropped slightly between 2016 and the second quarter of 2023, while still exceeding 43%. At the same time, the median net wealth increased by approximately 40% (Chart 2).

Chart 2: Share of net wealth held by top 5% (left) and household median net wealth (right), euro area

Methodological notes

The DWA data and information on the methodology can be accessed via the ECB Data Portal.
DWA results are available from 2009 and combine the aggregated quarterly sector accounts (QSA) with the four available HFCS waves between 2010 and 2021. Results for the quarters after 2021 are estimated using the most recent sector accounts data and the latest available HFCS wave, assuming a stable instrument distribution. As a result, for recent quarters the DWA capture the impact of developments in sector accounts on wealth distribution, and provide an estimate for the distributional effect of price changes for each instrument. Possible further changes due to differences in the investment and financing behaviour of different household groups are not reflected and will be only integrated as subsequent HFCS waves are released.
DWA data are at current prices and are not adjusted for the effect of inflation.
The data will be updated every three months and will reflect any revisions to the QSA. Furthermore, data from 2021 onwards will be revised when the next HFCS wave becomes available.

Experimental data comply with many, but not all, of the quality requirements of official ECB statistics. A sensitivity analysis has been performed on some parameters used in the estimates, however the results may be subject to higher uncertainty compared with other statistics.

Wealth deciles are computed by ranking households of a country according to their net wealth, starting with the poorest ones, and then grouping them into ten consecutive subsets, each representing 10% of the population: D1 is the poorest decile according to net wealth, D2 the second poorest, etc… up to D10 which is the richest decile according to net wealth. Deciles D1 to D5 together form the “bottom 50%”.

The Gini coefficient measures the extent to which the distribution of wealth within a country deviates from a perfectly equal distribution. A coefficient of 0 expresses perfect equality where everyone has the same wealth, while a coefficient of 1 expresses full inequality where only one person has all the wealth.

 See the overview of the ECB’s monetary policy strategy.

Two of the recommendations for G-20 countries relate to developing distributional information on household income, consumption, savings and wealth in line with the national accounts. See recommendations III.8 and III.9 in https://www.imf.org/en/News/Seminars/Conferences/DGI/g20-dgi-recommendations#dgi3 .
Assets include: deposits, debt securities, equity, life insurance, housing wealth and non-financial business wealth. Liabilities mainly comprise loans received.

 
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ECB Blog post |  Catastrophes caused by climate change, such as rising sea levels or more frequent extreme weather events, will harm our economies. And this will put a strain on the finances of people, companies and governments alike. Because of the risks to individual banks, banking supervisors have already taken steps to enhance how banks identify, assess and manage these institution-specific risks.[1] Such supervisory measures are necessary steps focusing on the risks that climate change may pose to individual banks.
But climate change is also a risk to the broader financial system. The last two decades’ financial crises showed how the build-up of system-wide risk can erupt into costly turmoil. A timely macroprudential policy response is vital to strengthen the system’s resilience to climate-related risks.
Climate change as a systemic risk
Because of their unique nature, climate-related risks are likely to represent a systemic risk.[2] First, the impact of climate change is irreversible. Unlike the economic and financial losses caused by conventional business cycles, rising sea levels, changing precipitation and the loss of arable or liveable land cannot be reversed. Second, the breadth of physical and transition risks mean they might simultaneously and unpredictably affect a significant share of financial institutions across sectors and/or countries.
While financial exposures to climate change are concentrated, they are not isolated. It has been clearly established that climate risks are highly concentrated. For example, high-emission sectors are over 70% of corporate lending of euro area banks. They are also expected to account for two-thirds of banks’ losses in the transition to a lower-carbon economy. These losses are unlikely to be isolated and contained.
Disruptions resulting from climate change are likely to spread along global production value chains and through financial portfolios. For example harder-to-diversify risks will result in a growing insurance protection gap. That could create a negative feedback loop: banks might be reluctant to grant loans to households and companies in vulnerable areas or industries, which in turn might worsen the local ability to adapt to a changing climate.
Why a macroprudential approach is important
The discussion on the role and timing of a macroprudential response has just begun.[3] This is due primarily to uncertainty. Climate risks will eventually materialise, but their severity and form will depend on how climate change and the green transition unfold. While a wait-and-see approach might seem preferable until there is more clarity, this might delay action until it’s too late. Like other cases of systemic risk build-up, today’s underestimation of risks can result in capital misallocation and economic losses tied to the irreversibility of global warming. A macroprudential approach, aiming to reduce the accumulation of such risks, could counter this inaction bias through preventative (and not just corrective) action to contain financial risk.
Another challenge concerns the role of macroprudential policies in the broader policy mix. The progress made by microprudential supervisors and improvements in market participants’ risk management could lead to the misperception that no further action is needed. But this approach is not enough, because climate change will also likely affect risks that cut across the financial system, with financial risks that emanate from collective and not just individual actions. More frequent and severe weather events, for example, will make the negative economic impacts more volatile. Likewise, the transition to a low-carbon economy might be bumpy, with volatility around insufficiently prepared parts of the financial system. This may require additional resilience to account for the increase in system-wide risks that are currently not captured in the prudential framework for supervision of individual banks. Macroprudential policy would complement microprudential measures by both reducing risk build-up and increasing resilience against growing climate risks.
Analytical advances and the development of a shared monitoring framework have significantly improved our ability to understand and manage climate-related financial risks.[4] With the progress being made on the analytical side, developing a common EU macroprudential policy framework is both timely and possible.
Towards a common macroprudential strategy for climate risks
The 2022 ECB-ESRB Project Team report, The macroprudential challenge of climate change, looked at the possible macroprudential response and possible instruments to be used. The 2023 Project Team report will follow up by outlining a comprehensive common EU strategy for macroprudential policies to address climate risks, including a menu of specific policy options ready to be used when necessary.
The framework can use tools to address risks from a lender’s perspective (e.g. general or sectoral capital buffers, concentration thresholds), as well as from a borrowers’ perspective, or with tools targeting informational failures (e.g. enhanced disclosures). The complex and evolving nature of climate risks means an effective macroprudential framework also needs to be adjusted as the understanding of climate risks evolve: they may be scaled up if risks increase, and scaled down if and when risks recede.
The macroprudential response needs to be targeted, gradual and dynamic. The ideal response must prioritise aligning incentives with the prudential objectives. Imposing restrictive capital requirements indiscriminately may unintentionally hinder the financing of the green transition. Taking into account corporates’ forward looking transition plans could make macroprudential tools more efficient and limit possible side effects.
A common framework is key to ensure a consistent policy response. Close coordination across jurisdictions at the European level and beyond will be crucial to maximise efficiency.
Macroprudential policies can complement microprudential policies and ensure that the financial system is robust and resilient in the face of climate-related financial risk. By doing so, they will also ensure that the financial system is able to fulfil its role of financing the economy and the transition to climate neutrality. And, as highlighted in the ECB’s recent second economy-wide climate stress test exercise, the sooner and faster we complete the necessary green transition, the lower the overall costs and risks.
The views expressed in each blog entry are those of the authors and do not necessarily represent the views of the European Central Bank and the Eurosystem.
Check out The ECB Blog.
 

Footnotes:

In 2020 the ECB published its Guide on climate and environmental risks setting out its supervisory expectation in that regard, and in 2022 the Basel Committee on Banking Supervision adopted Principles for the effective management and supervision of climate risks.
FSB (2022). Supervisory and Regulatory Approaches to Climate-related Risks. Final report. 13 October 2022.
The 2022 ECB-ESRB Project Team report The macroprudential challenge of climate change provided a first contribution to the development of concrete policy options. Beyond the EU, the Bank of England and the Prudential Regulation Authority discussed an “escalating” climate buffer, based on a risk assessment on the materiality of future system-wide transition and the physical risks associated with climate change.
ECB-ESRB (2022), The macroprudential challenge of climate change.

 
 
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