Member states’ EU ambassadors today agreed on the Council’s partial negotiating mandate on the proposed Strategic Technologies for Europe Platform (STEP).
The platform will support investments in critical technologies in the fields of digital and deep tech, clean tech and biotech in the EU. It will reduce the EU’s strategic dependencies and enhance its long-term competitiveness.
The Council’s negotiating mandate is partial, because its position on additional financial support for STEP will depend on the final outcome of the horizontal negotiations on the mid-term revision of the multiannual financial framework for 2021-2027.
Main elements of the Council’s mandate
In its mandate, the Council clarifies the objectives and scope of STEP, and confirms its support for the proposed sovereignty seal and sovereignty portal for STEP-related investments.
To facilitate the use of available funding and create synergies among funding instruments for investments in critical technologies, the Council supports identifying resources which would support STEP objectives within a range of existing EU programmes and funds, including the InvestEU, Horizon Europe, European Defence Fund, Innovation Fund, Recovery and Resilience Facility and cohesion policy funds.
The Council also agrees to the Commission proposal to apply a 100 % co-financing rate and a 30 % pre-financing for STEP priorities under the 2021–2027 programming period for cohesion policy funds, as well as to the proposal to enable investments in large enterprises.
Considering the continued budgetary pressure in member states, the Council has also agreed to apply retroactively a 100 % co-financing rate to the 2014-2020 cohesion programmes in the final accounting year, whilst extending the deadline for submitting payment applications by 12 months.
In addition, the Council has included in its mandate some other provisions to reduce administrative burden for the member states and facilitate the reprogramming of funds towards STEP objectives.
Next steps
The partial mandate agreed today will serve as a basis for negotiations on STEP with the European Parliament. Once an agreement with the Parliament is reached, the regulation will need to be formally adopted by the Council and the European Parliament.
Background
The Commission proposed the creation of a Strategic Technologies for Europe Platform on 20 June 2023 as part of its package of proposals related to the mid-term revision of the multiannual financial framework 2021-2027.
Today the Council also agreed a partial negotiating mandate on the Ukraine Facility.
 
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Cheaper cross-border payment services would benefit people and economies worldwide
Kieran Murphy
January 3, 2024

Faster, cheaper, and more transparent cross-border payment services have the potential to improve many lives by supporting economic growth, international trade, global development, and financial inclusion. The Group of Twenty has prioritized such progress.
That’s because the financial links between countries, particularly between emerging market and developing economies, face several challenges that must be addressed, including high costs and inconsistent charges depending on the countries being linked, as we explore in a new paper prepared as part of our payments work with the G20.
The global average cost of sending $200 from one country to another is about $12.50 in the first quarter of 2023, or 6.25 percent, according to the World Bank’s Remittance Prices Worldwide database. The G20 have set a target, reaffirming the United Nations Sustainable Development Goal, of a global average cost for sending a $200 remittance of no more than 3 percent by 2030, with no corridors higher than 5 percent.
However, as the Chart of the Week shows, some costs are many times higher than this target. Fees exceed 50 percent for funds sent from Türkiye to neighboring Bulgaria, for example. Costs are notably high for sending money in sub-Saharan Africa, where Tanzanian remittances to Uganda and Kenya incur fees over 30 percent. In South Africa, it’s particularly costly to send across its borders with Botswana, Eswatini, and Lesotho.

High fees, especially bank-to-bank transfers, are a main driver of the high costs for corridors between emerging market and developing economies. Such bank fees tend to be much lower for transfers originating in advanced economies where foreign-exchange margins can be 50 percent or more of the cost in some corridors.
The Financial Stability Board acknowledged in a recent report that progress under the roadmap to enhance cross-border payments will be needed to meet the targets set across the wholesale, retail, and remittances market segments.
To help reduce costs and address challenges with cross-border payments, international organizations such as the IMF and World Bank will need to play a key role by sharing best practices through technical assistance for member countries. Technical assistance can help because, while the targets are set at a global level, they require coordinated and customized assistance at the country level to address specific challenges.
The IMF shares its knowledge with government institutions such as finance ministries and central banks through hands-on advice, training, and peer-to-peer learning. Our technical assistance is part of capacity development, which is a core mandate that accounts for nearly a third of the IMF budget.
We will focus in coming years on improving access to payment systems, extending and aligning operating hours, interlinking of payment systems, combating money laundering and the financing of terrorism, and harmonizing payment systems by adopting the global and open standard for exchanging financial information, known as ISO 20022. We will also collaborate with the World Bank at the country and project level.

 
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NEW YORK—The Federal Reserve Bank of New York’s Center for Microeconomic Data today released the December 2023 Survey of Consumer Expectations, which shows that inflation expectations declined at the short-, medium- and longer-term horizons. Notably, inflation expectations at the short-term horizon reached the lowest level recorded since January 2021. Earnings growth and spending growth expectations also decreased slightly to their lowest recorded levels since 2021, while expectations about credit access and households’ financial situation turned less pessimistic.

The main findings from the December 2023 Survey are:
Inflation

Median inflation expectations declined at all horizons, falling to 3.0% from 3.4% at the one-year ahead horizon, to 2.6% from 3.0% at the three-year ahead horizon, and to 2.5% from 2.7% at the five-year ahead horizon. Median inflation expectations at the one-year ahead horizon reached the lowest level recorded since January 2021. The survey’s measure of disagreement across respondents (the difference between the 75th and 25th percentile of inflation expectations) increased at the one-year ahead horizon, and decreased at the three-year and five-year ahead horizons.
Median inflation uncertainty—or the uncertainty expressed regarding future inflation outcomes—remained essentially unchanged at all three horizons.
Median home price growth expectations remained unchanged at 3.0%, remaining well above the series 12-month trailing average of 2.4%.
Median year-ahead expected price changes increased by 0.5 percentage point for the cost of a college education to 6.3%, decreased by 0.3 percentage point for food to 5.0%, decreased by 0.7 percentage point for rent to 7.3%, and remained flat for gas at 4.5% and the cost of medical care at 9.1%.

Labor Market

Median one-year-ahead expected earnings growth decreased by 0.2 percentage point to 2.5%, the lowest level since April 2021. The decline was driven by respondents with at most a high school diploma.
Mean unemployment expectations—or the mean probability that the U.S. unemployment rate will be higher one year from now—decreased by 1.4 percentage points to 37.0% , remaining below the series 12-month trailing average of 39.5%.

The mean perceived probability of losing one’s job in the next 12 months decreased slightly by 0.2 percentage points to 13.4%, remaining above the series 12-month trailing average of 12.3%. The mean probability of leaving one’s job voluntarily in the next 12 months increased by 0.8 percentage point to 20.4%.
The mean perceived probability of finding a job (if one’s current job was lost) increased marginally to 55.9% from 55.2% in November.

Household Finance

Median expected growth in household income decreased by 0.1 percentage point to 3.0%, remaining above the February 2020 pre-pandemic level of 2.7% . The series has been moving within a narrow range of 2.9% to 3.3% since January 2023.
Median household spending growth expectations declined by 0.2 percentage point to 5.0%, reaching the lowest level recorded since September 2021. Still, the series remains well above its February 2020 pre-pandemic level of 3.1%.
Perceptions of credit access compared to a year ago were largely unchanged. Expectations about credit access a year from now instead improved with a larger share of respondents expecting looser credit conditions and a smaller share of respondents expecting tighter credit conditions a year from now.
The average perceived probability of missing a minimum debt payment over the next three months increased by 0.6 percentage point to 12.4% , a level above the series 12-month trailing average of 11.5% but comparable to those prevailing just before the pandemic.
The median expected year-ahead change in taxes at current income level remained unchanged at 4.1%.
Median year-ahead expected growth in government debt decreased to 9.4% from 10% in November.
The mean perceived probability that the average interest rate on saving accounts will be higher in 12 months decreased by 3.6 percentage points to 25.9%, its lowest level since November 2021.
Perceptions about households’ current financial situations improved with fewer respondents reporting being worse off than a year ago. Year-ahead expectations also improved with a smaller share of respondents expecting to be worse off and a larger share of respondents expecting to be better off a year from now.
The mean perceived probability that U.S. stock prices will be higher 12 months from now increased by 0.2 percentage point to 36.7%.

About the Survey of Consumer Expectations (SCE)
The SCE contains information about how consumers expect overall inflation and prices for food, gas, housing, and education to behave. It also provides insight into Americans’ views about job prospects and earnings growth and their expectations about future spending and access to credit. The SCE also provides measures of uncertainty regarding consumers’ outlooks. Expectations are also available by age, geography, income, education, and numeracy.
The SCE is a nationally representative, internet-based survey of a rotating panel of approximately 1,300 household heads. Respondents participate in the panel for up to 12 months, with a roughly equal number rotating in and out of the panel each month. Unlike comparable surveys based on repeated cross-sections with a different set of respondents in each wave, this panel allows us to observe the changes in expectations and behavior of the same individuals over time. For further information on the SCE, please refer to an overview of the survey methodology here, the interactive chart guide, and the survey questionnaire.

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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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Beginning in the 18th century, the Industrial Revolution ushered in a series of innovations that transformed society. We may be in the early stages of a new technological era—the age of generative artificial intelligence (AI)—that could unleash change on a similar scale.
History, of course, is filled with examples of technologies that left their mark, from the printing press and electricity to the internal combustion engine and the internet. Often, it took years—if not decades—to comprehend the impact of these advances. What makes generative AI unique is the speed with which it is spreading throughout society and the potential it has to upend economies—not to mention redefine what it means to be human. This is why the world needs to come together on a set of public policies to ensure AI is harnessed for the good of humanity.
The rapidly expanding body of research on AI suggests its effects could be dramatic. In a recent study, 453 college-educated professionals were given writing assignments. Half of them were given access to ChatGPT. The results? ChatGPT substantially raised productivity: the average time taken to complete the assignments decreased by 40 percent, and quality of output rose by 18 percent.
If such dynamics hold on a broad scale, the benefits could be vast. Indeed, firm-level studies show AI could raise annual labor productivity growth by 2–3 percentage points on average: some show nearly 7 percentage points. Although it is difficult to gauge aggregate effect from these types of studies, such findings raise hopes for reversing the decline in global productivity growth, which has been slowing for more than a decade. A boost to productivity could raise incomes, improving the lives of people around the world.
But it is far from certain the net impact of the technology will be positive. By its very nature, we can expect AI to shake up labor markets. In some situations, it could complement the work of humans, making them even more productive. In others, it could become a substitute for human work, rendering certain jobs obsolete. The question is how these two forces will balance out.
A new IMF working paper delved into this question. It found that effects could vary both across and within countries depending on the type of labor. Unlike previous technological disruptions that largely affected low-skill occupations, AI is expected to have a big impact on high-skill positions. That explains why advanced economies like the US and UK, with their high shares of professionals and managers, face higher exposure: at least 60 percent of their employment is in high-exposure occupations.
On the other hand, high-skill occupations can also expect to benefit most from the complementary benefits of AI—think of a radiologist using the technology to improve her ability to analyze medical images. For these reasons, the overall impact in advanced economies could be more polarized, with a large share of workers affected, but with only a fraction likely to reap the maximum productivity benefits.
Meanwhile, in emerging markets such as India, where agriculture plays a dominant role, less than 30 percent of employment is exposed to AI. Brazil and South Africa are closer to 40 percent. In these countries, the immediate risk from AI may be reduced, but there may also be fewer opportunities for AI-driven productivity boosts.
Over time, labor-saving AI could threaten developing economies that rely heavily on labor-intensive sectors, especially in services. Think of call centers in India: tasks that have been offshored to emerging markets could be re-shored to advanced economies and replaced by AI. This could put developing economies’ traditional competitive advantage in the global market at risk and potentially make income convergence between them and advanced economies more difficult.
Redefining human
Then there are, of course, the myriad ethical questions that AI raises.
What’s remarkable about the latest wave of generative AI technology is its ability to distill massive amounts of knowledge into a convincing set of messages. AI doesn’t just think and learn fast—it now speaks like us, too.
This has deeply disturbed scholars such as Yuval Harari. Through its mastery of language, Harari argues, AI could form close relationships with people, using “fake intimacy” to influence our opinions and worldviews. That has the potential to destabilize societies. It may even undermine our basic understanding of human civilization, given that our cultural norms, from religion to nationhood, are based on accepted social narratives.
It’s telling that even the pioneers of AI technology are wary of the existential risks it poses. Earlier this year, more than 350 AI industry leaders signed a statement calling for global priority to be placed on mitigating the risk of “extinction” from AI. In doing so, they put the risk on par with pandemics and nuclear wars.
Already, AI is being used to complement judgments traditionally made by humans. For example, the financial services industry has been quick to adapt this technology to a wide range of applications, including introducing it to help conduct risk assessments and credit underwriting and recommend investments. But as another recent IMF paper shows, there are risks here. As we know, herd mentality in the financial sector can drive stability risks, and a financial system that relies on only a few AI models could put herd mentality on steroids. In addition, a lack of transparency behind this incredibly complex technology will make it difficult to analyze decisions when things go wrong.
Data privacy is another concern, as firms could unknowingly put confidential data into the public domain. And knowing the serious concerns about embedded bias with AI, relying on bots to determine who gets a loan could exacerbate inequality. Suffice it to say, without proper oversight, AI tools could actually increase risks to the financial system and undermine financial stability.
Public policy responses
Because AI operates across borders, we urgently need a coordinated global framework for developing it in a way that maximizes the enormous opportunities of this technology while minimizing the obvious harms to society. That will require sound, smart policies—balancing innovation and regulation—that help ensure AI is used for broad benefit.
Legislation proposed by the EU, which classifies AI by risk levels, is an encouraging step forward. But globally, we are not on the same page. The EU’s approach to AI differs from that of the US, whose approach differs from that of the UK and China. If countries, or blocs of countries, pursue their own regulatory approach or technology standards for AI, it could slow the spread of the technology’s benefits while stoking dangerous rivalries among countries. The last thing we want is for AI to deepen fragmentation in an already divided world.
Fortunately, we do see progress. Through the G7’s Hiroshima AI process, the U.S. executive order on AI, and the UK AI Safety Summit, countries have demonstrated a commitment to coordinated global action on AI, including developing and—where needed—adopting international standards.
Ultimately, we need to develop a set of global principles for the responsible use of AI that can help harmonize legislation and regulation at the local level.
In this sense, there is a parallel to cooperation on the shared global issue of climate change. The Paris Agreement, despite its limitations, established a shared framework for tackling climate change, something we could envision for AI too. Similarly, the Intergovernmental Panel on Climate Change—an expert group tracking and sharing knowledge about how to deal with climate change—could serve as a blueprint for such a group on AI, as others have suggested. I am also encouraged by the UN’s call for a high-level advisory body on AI as part of its Global Digital Compact, as this would be another step in the right direction.
Given the threat of widespread job losses, it is also critical for governments to develop nimble social safety nets to help those whose jobs are displaced and to reinvigorate labor market policies to help workers remain in the labor market. Taxation policies should also be carefully assessed to ensure tax systems don’t favor indiscriminate substitution of labor.
Making the right adjustments to the education system will be crucial. We need to prepare the next generation of workers to operate these new technologies and provide current employees with ongoing training opportunities. Demand for STEM [science, technology, engineering, and math] specialists will likely grow. However, the value of a liberal arts education—which teaches students to think about big questions facing humanity and do so by drawing on many disciplines—may also increase.
Beyond those adjustments, we need to place the education system at the frontier of AI development. Until 2014, most machine learning models came from academia, but industry has since taken over: in 2022, industry produced 32 significant machine learning models, compared with just three from academia. As building state-of-the-art AI systems increasingly requires large amounts of data, computer power, and money, it would be a mistake not to publicly fund AI research, which can highlight the costs of AI to societies.
As policymakers wrestle with these challenges, international financial institutions (IFIs), including the IMF, can help in three important areas.
First, to develop the right policies, we must be prepared to address the broader effects of AI on our economies and societies. IFIs can help us better understand those effects by gathering knowledge at a global scale. The IMF is particularly well positioned to help through our surveillance activities. We are already doing our part by pulling together experts from across our organization to explore the challenges and opportunities that AI presents to the IMF and our members.
Second, IFIs can use their convening power to provide a forum to share successful policy responses. Sharing information about best practices can help to build international consensus, an important step toward harmonizing regulations.
Third, IFIs can bolster global cooperation on AI through our policy advice. To ensure all countries reap the benefits of AI, IFIs can promote the free flow of crucial resources—such as processors and data—and support the development of necessary human and digital infrastructure. It will be important for policymakers to carefully calibrate the use of public instruments; they should support technologies at an early stage of development without inducing fragmentation and restrictions across countries. Public investment in AI and related resources will continue to be necessary, but we must avoid lapsing into protectionism.
An AI future
Because of AI’s unique ability to mimic human thinking, we will need to develop a unique set of rules and policies to make sure it benefits society. And those rules will need to be global. The advent of AI shows that multilateral cooperation is more important than ever.
It’s a challenge that will require us to break out of our own echo chambers and consider the broad interest of humanity. It may also be one of the most difficult challenges for public policy we have ever seen.
If we are indeed on the brink of a transformative technological era akin to the Industrial Revolution, then we need to learn from the lessons of the past. Scientific and technological progress may be inevitable, but it need not be unintentional. Progress for the sake of progress isn’t enough: working together, we should ensure responsible progress toward a better life for more people.

Author: Gita Gopinath, First Deputy Managing Director, IMF.

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IMF Blog post |  Policymakers need fuller view of consequences of illicit flows, including tallies of the fiscal, monetary, financial, and structural costs.
The fight against financial crime isn’t lost, but the world needs to do more to limit the economic impact of crime.
Money laundering is a necessary component of the organized crime that too frequently spans borders, skirts taxes, funds terrorism and corrupts officials—and it comes with hefty macroeconomic costs. Bad actors are also embracing new technologies on top of their traditional techniques, all of which makes economic growth less inclusive and sustainable, fueling inequality and informality.
The international community has made significant progress toward strengthening safeguards against money laundering and terrorist financing, with help from the IMF and other organizations. We decided a decade ago to take a more bespoke approach to identifying key risks, working with member countries and international partners, particularly, the Financial Action Task Force, the international standard-setter in this area.
But the overall efforts are still broadly insufficient. For example, as the FATF noted last year, there is still a major gap between progress countries have made on technical compliance, such as enacting new laws, and on the effectiveness of these efforts. For example, very little laundered ill-gotten proceeds are ever confiscated.
Accordingly, the IMF recently reviewed our strategy on anti-money laundering and combatting the financing of terrorism (AML/CFT). The goal is to better help our 190 member economies address these critical financial integrity issues.
High costs
We must first recognize that financial crime affects lives and livelihoods, especially those of the most vulnerable, and that the costs it imposes are very high—and increasing. Direct costs vary and can include lower revenues, higher expenditures, sanctions, lost banking services, and even increased financial instability.
For example, and as recent IMF work has shown in the Nordic Baltic Region, AML/CFT deficiencies are associated not only with large drops in stock prices for the most directly affected banks, but also declines in share prices of other lenders who simply happen to be in the same country, as well as banks in the region that have similar cross-border exposures.

The indirect costs are even greater because they are imposed across an economy, whether by fueling boom-and-bust cycles or making home prices unaffordable. Potential financial stability impacts include bank runs and lost foreign investment. Large-scale money laundering can even spur volatility in international capital flows, undermine good governance, spark political instability, and just generally erode trust—in governments and institutions.
Liquidity, as measured by deposit flows, tends to deteriorate around financial integrity events for the affected bank while other domestic banks’ liquidity could benefit from positive substitution effects in the short-term.

Another important consideration is that illicit financial flows are a global problem. Insufficient AML/CFT frameworks in some countries, including international financial centers, can attract criminal proceeds from abroad. In countries exporting illicit flows, we see there is less opportunity, higher inequality, higher poverty, more illegal immigration, misused resources, and environmental degradation. For example, one study shows that illicit financial flows in Africa (an estimated $1.3 trillion since 1980 has left sub-Saharan Africa) drain domestic revenues that could be used for the continent’s development, have a strong and negative effect on investment rates, notably private investment, and are curtailing Africa’s savings rate. These effects can also have a cascading effect on countries transiting or receiving the illicit proceeds.
This underscores why we must better understand how money laundering and terrorist financing can hurt individuals, countries, and even the global economy. And because of the wide-ranging consequences, we are deepening AML/CFT considerations across all the work that we do, while urging our members to safeguard their financial sectors and broader economy to help ensure global financial stability.
Deeper understanding
Analysis of money laundering and terrorist financing historically focused on threats and vulnerabilities. Both are central to gauging and containing risks, but more is needed. Knowing the full extent of consequences for economies requires being able to understand the fiscal, monetary, financial sector and structural costs of illicit flows. This is needed to document just how financial integrity affects both a given country’s financial stability and broader economy, plus how global financial stability might be affected.
Accordingly, the IMF Executive Board has endorsed a plan for the institution to expand its data analytics capacity to focus on these issues and deepen the coordinated approach across all of our key work areas, including IMF surveillance, lending engagements, capacity development and Financial Sector Assessment Programs. This new approach will also give the IMF new evidence to answer key questions including:

Which sectors are most vulnerable for money laundering, from banks and real estate to virtual assets and precious metals?
What countries export illicit flows, allow them to transit, and what countries integrate them?
How do these illicit flows affect the economy, including its prospects for inclusive and sustainable growth and development?

Even after decades of progress in financial integrity, the Fund and the international community must persist and press on in this fight. Crime is a moving target, but we can—and must—broaden and deepen our containment efforts. This includes improving cooperation among stakeholders, including governments, international bodies, and civil society. For our part, the IMF will use its strength as a macroeconomic institution with global reach to help its members assess the impact of financial crimes and illicit flows and design and implement policies to address them. The cost of failure is simply too high.
—See our new AML/CFT page for the recent Executive Board paper: 2023 Review of the Fund’s Anti-Money Laundering and Combating the Financing of Terrorism Strategy and the background papers.
 
For more information, please contact the authors:
> Carolina Claver, Senior Financial Sector Expert – Financial Integrity Group, IMF
> Chady El Khoury, Deputy-Unit Chief of the Financial Integrity Group, IMF
> Rhoda Weeks-Brown, General Counsel and Director –  Legal Department, IMF
 
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High energy prices triggered by Russia’s war of aggression against Ukraine prompted governments to reduce excise taxes during 2022, leading to lower tax levels in many countries, according to new OECD analysis.
Revenue Statistics 2023 shows that the average tax-to-GDP ratio in the OECD fell by 0.15 percentage points (p.p.) in 2022, to 34.0%. This was only the third such decline since the Global Financial Crisis in 2008-09: the level fell by 0.6 p.p. in 2017 and by 0.1 p.p. in 2019.
Revenues from excise taxes fell as a share of GDP in 2022 in 34 of the 36 countries for which preliminary data is available, declining in absolute terms in 21 of these. In some countries, notably in Europe, these declines were related to reductions in energy taxes as well as lower demand for energy products. Revenues from value-added tax (VAT) also declined as a share of GDP in 19 countries, in part due to policies to cushion consumers against high prices for energy and food.
The decline in revenues from excise taxes in 2022 was partly offset by increases in revenues from corporate income taxes (CIT), which rose as a share of GDP in more than three-quarters of OECD countries amid higher corporate profits, especially in the energy and agricultural sectors. CIT revenues in Norway rose by 8.8% of GDP due to exceptional profits in the energy sector.
Overall tax revenues declined as a share of GDP in 21 of the 36 countries in 2022, increased in 14 countries and remained at the same level in one. The largest decline was observed in Denmark (-5.5 p.p., to 41.9%) while the largest increases were seen in Korea (2.2 p.p., to 32.0%) and Norway (1.8 p.p., to 44.3%).
The decline in the OECD’s average tax-to-GDP ratio followed two years of increases during the COVID-19 pandemic, of 0.15 p.p. in 2020 and 0.6 p.p. in 2021. Tax-to-GDP ratios in 2022 ranged from 16.9% in Mexico to 46.1% in France.
A special feature in the new report examines the extent to which tax revenues in OECD countries have kept pace with economic growth in recent decades by analysing tax buoyancy for different tax types for the period from 1980 to 2021. The study finds that tax revenues typically increased at the same rate as GDP over this period; revenues from CIT were the most buoyant over the long run – increasing faster than economic growth – while revenues from excise taxes were the least buoyant, increasing at a slower rate than GDP.
To access the Revenue Statistics report, data, overview and country notes, go to https://oe.cd/revenue-statistics.
 
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IMF Blog post |  Ensuring a lower-carbon future is not only necessary but also good for the economy, according to the latest climate scenarios from the Network for Greening the Financial System, a group of 127 central banks and financial supervisors working to manage climate risks and boost green investment.
The NGFS data come as world leaders gather in Dubai for the 28th United Nations Climate Change Conference, or COP28, to forge agreement on how to keep the planet from overheating.
As the Chart of the Week shows, making an orderly transition to net zero by 2050 could result in global gross domestic product being 7 percent higher than under current policies.

This year will be the warmest on record, according to the World Meteorological Organization. While temperatures are rising unevenly across the world, on average they are up 1.2 degrees Celsius from pre-industrial levels.
Economic and financial risks are rising too. NGFS models show that droughts and heatwaves are the largest source of risk across regions. Specifically, countries in Europe and Asia are most exposed to heatwaves, while countries in Africa, North America, and the Middle East are most vulnerable to droughts.
Transitioning to a low-carbon economy will have negative impacts on demand from higher carbon prices and energy costs. But these can be partially offset by recycling carbon revenues into government investment and lower employment taxes. Most importantly, lowering emissions will reduce the physical impacts of climate change, which lowers macroeconomic costs.
Transitioning to a net-zero economy will require substantial investment in green electricity and energy storage. How economies approach making this investment poses policy tradeoffs, as detailed in the October Fiscal Monitor.
The NGFS, established in 2017, aims to strengthen the global response in meeting Paris Agreement goals and helping the financial system manage risks. The climate scenarios, which are aligned with international best practices, supplement those of other international organizations such as the Intergovernmental Panel on Climate Change and the International Energy Agency.
The IMF is one of 20 international organizations that are NGFS observers, and actively contributes to the scenario design and analysis. A selection and visualization of key indicators from the NGFS climate scenarios is curated by the IMF on the Climate Change Indicators Dashboard.
 
For more information, please contact the author:
> Jens Mehrhoff, Senior Economist – Statistics Department, IMF
 
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