Call for applications: Klaus Liebscher Economic Research Scholarship

The scholarship program targets Austrian and international experts with a proven research record in economics and finance, and postdoctoral research experience. Applicants need to be in active employment and should be interested in broadening their research experience and expanding their personal research ­networks. Given the OeNB’s strategic research focus on Central, Eastern and Southeastern Europe, the analysis of economic developments in this region will be a key field of research in this context.

The OeNB offers a stimulating and professional research environment in close proximity to the policymaking process. The selected scholarship recipients will be expected to collaborate with the OeNB’s research staff on a prespecified topic and are invited to participate actively in the department’s internal seminars and other research activities. Their research output may be published in one of the department’s publication outlets or as an OeNB Working Paper. As a rule, the consultancy services under the scholarship will be provided over a period of two to three months. As far as possible, an adequate accommodation for the stay in Vienna will be provided. ¹

Applicants must provide the following documents and information:

• a letter of motivation, including an indication of the time period envisaged for the consultancy
• a detailed consultancy proposal
• a description of current research topics and activities
• an academic curriculum vitae
• an up-to-date list of publications (or an extract therefrom)
• the names of two references that the OeNB may contact to obtain further information about the applicant
• evidence of basic income during the term of the scholarship (employment contract with the applicant’s home institution)
• written confirmation by the home institution that the provision of consultancy services by the applicant is not in violation of the applicant’s employment contract with the home institution

Recent economic developments and outlook

Developments in selected CESEE countries

Coronavirus sends CESEE region into a deep recession ^{2 , 3 , 4}

1 Regional overview

Despite the depth of the GDP decline, the CESEE region reported more benign growth figures than the euro area (–7.3% compared to –11.8% in the second quarter of 2020, quarter on quarter, see table 1). The more gradual spread of the pandemic eastward in spring and the quick reaction by local authorities prevented the type of public health crises that were observed in e.g. Italy or Spain and enabled CESEE to start lifting restrictions on public life and the economy at a comparatively early stage. This led to a somewhat smaller contraction of domestic demand (especially investments) in many countries, which explains some of the growth advantage vis-à-vis the euro area. The regional average was also heavily influenced by the rather small GDP contraction of the Russian economy (–3.2% in the second quarter, quarter on quarter). Russia benefited from a large positive growth contribution of net exports, as low domestic demand and ruble depreciation depressed imports. At the same time, export volumes of certain key products started to increase already in the spring, thanks in part to the rapid recovery of the Chinese economy.

At the same time, Croatia and Hungary were among the countries in Europe that were hit most severely by the COVID-19 pandemic in terms of GDP loss. This underlines the heterogeneity of current economic developments in the region. In Croatia, the sharp decline was mostly driven by tourism, which accounts for around one-quarter of the country’s GDP (including indirect contributions). In Hungary, car production, tourism and transportation services weighed on growth.

In general, contact-intensive sectors (hospitality, travel and tourism) and those with complex value chains (electronics and automobiles) suffered the most throughout CESEE. Restricted cross-border mobility tremendously lowered hotel occupancy rates over the summer. In the automobile sector, factory shutdowns led to a decline of European car production by more than one-third in the first half of 2020 (when compared to a year earlier). This imposed a heavy burden on several CESEE countries where the automobile sector accounts for a large share of industrial production (besides Hungary also the Czech Republic, Romania and Slovakia).

Table 1: Real GDP growth  

	2017	2018	2019	Q1 19	Q2 19	Q3 19	Q4 19	Q1 20	Q2 20
	Period-on-period change in %, seasonally and working day adjusted
Slovakia	3.0	3.9	2.4	0.6	0.4	0.4	0.6	–5.2	–8.3
Slovenia	4.8	4.4	3.2	0.9	0.0	0.8	0.4	–4.7	–9.9
Bulgaria	3.5	3.1	3.4	1.0	0.7	0.7	0.8	0.3	–10.0
Croatia	3.1	2.7	2.9	1.1	0.6	0.6	0.4	–1.3	–14.9
Czech Republic	5.2	3.2	2.3	0.5	0.5	0.5	0.4	–3.3	–8.7
Hungary	4.3	5.1	4.9	1.9	0.8	0.9	0.7	–0.4	–14.5
Poland	4.9	5.3	4.1	1.4	0.7	1.2	0.2	–0.4	–8.9
Romania	7.1	4.4	4.1	1.5	0.6	0.5	1.2	0.3	–12.3
Turkey	7.5	3.0	0.9	1.3	1.2	0.4	1.9	0.6	–11.0
Russia	1.8	2.5	1.3	–0.5	2.4	–0.9	–0.7	–0.9	–3.2
CESEE average1	4.0	3.2	2.1	0.5	1.5	0.0	0.3	–0.6	–7.3
Euro area	2.5	1.9	1.2	0.5	0.1	0.3	0.1	–3.7	–11.8
Source: Eurostat, national statistical offices.
1 Average weighted with GDP at PPP.

A look at the expenditure side of GDP shows that all countries of the region reported a notable reduction of domestic demand (see chart 1). Private consumption suffered from deteriorating sentiment, movement restrictions, (temporary) closures of nonessential shops and social distancing measures to contain COVID-19 infections. Furthermore, incipient labor market weaknesses also impacted on consumer spending, as furlough schemes and reduced working hours weighed on disposable income and unemployment was on the rise. The average unemployment rate of the region increased from 6.3% at the end of 2019 to 7.7% in August 2020, the highest level in five years.

This figure, however, still underestimates the current slack in the labor market. It is based on the International Labour Organization’s standard definition of unemployment, which counts as unemployed people without a job who have been actively seeking work in the last four weeks and are available to start work within the next two weeks. The COVID-19 outbreak and the measures applied to contain it have impacted on both the ability to seek work (e.g. due to a lockdown) and the availability to start work (e.g. due to care obligations toward family members). Furthermore, active measures to contain employment losses have led to absences from work rather than dismissals (e.g. in the case of furlough schemes).

An indicator of the actual labor market slack provided by Eurostat (not available for Russia) reveals that persons with an unmet need for employment ⁵ accounted for an average of 13.5% of the extended CESEE labor force in the second quarter of 2020. This figure was up 2.6 percentage points from the first quarter of 2020, which represented the strongest increase since the start of the series in 2008.

In the second quarter of 2020, absences from work more than tripled against the first quarter, amounting to a total of more than 3.8 million people in the CESEE region (again excluding Russia). As a percentage of total employment, the figure was especially high in Slovakia, Slovenia and Turkey (21.7%, 27.3% and 30.7%, respectively, in the second quarter of 2020). In the other countries, however, it remained below the EU average of 21.8%.

After capital spending had already been impaired by rising uncertainty concerning the further spread of coronavirus and a weak absorption of EU funds at the beginning of the year, it declined notably in the second quarter of 2020. This was related to generally weak demand conditions (internationally and at home), the disruption of international production chains and a sharp drop in corporate profits and capacity utilization. Furthermore, growth of credit to corporations decelerated strongly in the review period.

Public consumption was the only part of domestic demand that delivered (moderately) positive growth contributions in most countries of the region in the second quarter of 2020 against the background of large fiscal support for households and companies (see below).

Some regional heterogeneity could be observed in external sector developments. The closing of borders, travel restrictions and the economic malaise in large parts of the world led to a strong decline in exports. At the same time, however, imports declined notably as well, mirroring weak demand conditions at home. Consequently, net exports often weighed negatively on GDP growth in many countries. In Slovakia, Slovenia, Bulgaria and Romania the negative growth contribution was only moderate. However, in the Czech Republic and Turkey, net exports reduced GDP growth more strongly than domestic demand did. In contrast, in Poland and – as mentioned above – Russia, they contributed positively to growth.

Simultaneously with other European countries, the CESEE countries deployed large fiscal packages to support vulnerable households and firms, eased monetary policy to support the flow of credit and tackle financial market disruptions and adopted macroprudential measures that cushioned the impact of the crisis on both banks and borrowers.

Direct fiscal measures to mitigate the economic fallout from the coronavirus crisis included tax cuts, subsidies for wages and social security contributions, compensation for people in quarantine and firms affected by shutdown measures, higher allowances (e.g. for children) and bonuses (e.g. workers in health care), higher minimum wages and/or some sort of furlough schemes subsidizing wages and shorter work hours. The latter was imperative in preventing a sharper deterioration in labor market conditions. Furlough schemes covered up to 15% of the workforce in Slovenia, Turkey and Slovakia, up to 20% in Romania and about one-third in Croatia at their maximum usage.

Indirect fiscal measures included guarantees and deferrals for tax payments and social security contributions. Furthermore, all countries introduced moratoria on the repayment of loans to alleviate financial strains for borrowers. Concerning the latter, no more than 15% of borrowers renegotiated loan repayments in most ­CESEE countries. Even in countries where blanket moratoria were imposed by law (Hungary, Romania), penetration remained below 50% of private-sector loans. This is a sign that the remaining borrowers were able to service their debt amid falling interest rates and borrowing costs and despite the economic downturn.

The announced fiscal support was largest in the Czech Republic, with a package worth more than 20% of GDP. Rather large packages have also been deployed in Slovenia, Croatia, Hungary and Poland (of around 10% of GDP and more). The stimulus was comparatively moderate in Slovakia, Romania and Russia (at around 5% of GDP or below). As these numbers include direct as well as (in some cases very sizable) indirect measures (mainly guarantees and tax deferrals), the actual fiscal stimulus will crucially depend on the effective utilization of the available funds. Estimates of utilization by mid-September 2020 point to an already high usage in Turkey, Croatia, Hungary, Romania and Russia, while utilization remains more muted in the other countries. In addition to domestic spending, CESEE EU member states can make use of loans provided under the EU’s SURE instrument (Support to mitigate Unemployment Risks in an Emergency) that was designed to tackle sudden increases in public expenditure for the preservation of employment.

Monetary support in CESEE took the form of rate cuts, liquidity provision, quantitative easing and/or exchange rate stabilization. Since the escalation of the crisis in March, key policy rates were slashed throughout the region (in the Czech Republic by 200 basis points to 0.25%, in Poland by 140 basis points to 0.1%, in Hungary by 30 basis points to 0.6%, in Romania by 100 basis points to 1.5%, in Russia by 175 basis points to 4.25% and in Turkey by 250 basis points to 8.25%). To provide the banking sector with sufficient liquidity, central banks adjusted ­reserve requirements (e.g. in the Czech Republic, Croatia, Turkey), launched longer-term refinancing operations (e.g. in Croatia) and introduced new foreign currency-­providing operations (e.g. in Turkey). New arrangements with the ECB need to be mentioned, in particular. The central banks of Hungary and Romania agreed on new repo lines (EUR 4 billion and EUR 4.5 billion, respectively, until the end of June 2021) and the central banks of Croatia and Bulgaria agreed on new swap lines with the ECB (EUR 2 billion until the end of June 2021 and EUR 2 billion until the end of 2020). Furthermore, several central banks purchased bonds of their respective governments on the secondary market (e.g. in Poland, Hungary, Croatia, ­Romania and Turkey). Monetary authorities in Croatia and Russia also intervened in foreign exchange markets to ease depreciation pressures.

Banking sector regulation on liquidity, nonperforming exposures and reporting requirements was softened in many countries. Countercyclical capital and other mandatory capital buffers were reduced in the Czech Republic, Slovakia, Poland and Hungary. Several regulators also called on banks not to pay out dividends (e.g. in Hungary, Slovenia, Croatia and Bulgaria) and the Czech Republic adjusted its tool kit of borrower-based macroprudential measures.

Concerning general banking sector developments, the coronavirus pandemic brought about a reversal of previous years’ trends. Most importantly, a slowdown in credit growth was observed in nearly all countries of the region (see chart 2). The only notable exception was Turkey, where (mostly state-owned) banks boosted consumer lending in an attempt to mitigate the general economic contraction. In the other CESEE countries, weaker demand and worsening credit supply conditions impacted on credit dynamics. Demand suffered from the faltering general economic momentum and deleveraging needs in the private sector. Supply was negatively affected by the local and international macroeconomic environment, local capital constraints, groups’ funding and nonperforming exposures. While nonperforming loans (NPLs) have not yet embarked on an upward trend (also reflecting the policy measures outlined above), surveys among banks show that the quality of loan applications is expected to deteriorate sharply across the client spectrum and that NPLs are expected to increase markedly in the future.

The crisis has already had a notable impact on the profitability of the CESEE banking sectors. The average return on assets in mid-2020 was roughly 50% lower than a year earlier; in Slovenia and Hungary, it dropped to a quarter of the value seen a year before. Rising loan loss provisions in response to the recession were a main driver of lower profits. Profitability will remain under pressure in the coming quarters, as eased regulatory requirements and loan moratoria only temporarily sheltered banking sectors from some of the COVID-19-related impact. Moratoria affect the timing of banks’ interest income and the net present value of loans in countries where no interest can be charged on deferred payments. Central bank rate cuts put additional pressure on net interest margins and lower loan growth will weigh on operating income. Deteriorating profitability, coupled with rising NPLs, will likely weigh on banks’ capital ratios. As of mid-2020, however, most CESEE banking sectors continued to report substantial capital buffers.

Inflation has surprised on the upside since the gradual reopening of CESEE economies in the second quarter of 2020 in many countries (including the Czech Republic, Hungary, Poland, Romania, Turkey and Russia) – despite the strong ­decline in economic activity (see chart 3). As price developments were heavily ­influenced by deflation in the energy component in recent months, several countries (e.g. the Czech Republic, Hungary and Poland) even reported rising core­ ­inflation rates in the midst of a deep recession.

When interpreting these trends, it should be noted that price data collection has been affected by the COVID-19 crisis. During lockdown periods, actual market prices for many goods and services were not available and had to be estimated from close substitutes or historical data. COVID-19 has probably also led to problems with recording seasonal price patterns (e.g. for flights, package holidays and accommodation services, or when seasonal sales in certain retail segments were postponed or canceled). On top of that, the actual consumption basket has likely changed during the pandemic and these changes in consumption patterns are not yet reflected in the HICP.

Despite these caveats, unabated price pressures can be related to four factors: (1) Several CESEE currencies depreciated notably vis-à-vis the euro from March 2020 and retailers likely failed to reflect the effects of currency weakness in prices during lockdowns. (2) Administered price growth contributed positively to HICP dynamics in many CESEE countries as governments attempted to make up for at least a small part of missing budget revenues. (3) The lifting of the most severe restrictions released some pent-up demand. This sudden increase of demand met with incompletely restored production capacities in certain sectors (partly owing to disrupted supply chains), creating a mismatch between supply and demand (e.g. for certain industrial goods). (4) Capacity constraints related to social distancing measures and stepped up sanitary requirements contributed to price growth in certain service segments. Out of these four factors, currency depreciation has likely had the strongest effect on price growth, since inflation fell significantly in the euro area countries and in countries with a more stable or fixed exchange rate regime.

Price pressures, however, can be expected to moderate in the coming months as looser labor market conditions and weaker wage growth should start to weigh more strongly on core inflation. As of August 2020, inflation ran above the respective central bank targets in the Czech Republic, Hungary and Turkey. While the Czech and the Hungarian central banks expect a return to the target range until the end of 2020, the Turkish central bank expects inflation to remain elevated until late 2021.

Aggregate current account developments in the CESEE EU member states have so far only been little affected by the COVID-19 pandemic. In most countries, combined current and capital account balances remained broadly stable in mid-2020 when compared to the end of 2019 (see chart 4). Some changes in the composition of the current account, however, were visible. On the one hand, the lockdown-induced recession put a brake on profit outflows via the primary income account. On the other hand, trade and services balances tended to deteriorate somewhat in many countries, as external demand declined more strongly than ­domestic import demand.

Despite currency weaknesses, Russia and Turkey reported a clear deterioration of their external accounts. In Russia, a notable decline of energy prices – the most important export commodity of the country – pushed nominal export growth deep into the red. In Turkey, the trade and services balance deteriorated already in the first quarter of 2020, as the recovery from the recession of 2018 and 2019 was still gathering steam and fueled import demand. The spread of coronavirus and the subsequent containment measures caused both imports and exports to contract strongly in the second quarter of 2020. While imports held up somewhat better due to government policies aimed at shoring up the economy, exports were severely impacted by the weak international environment and a sharp decline in foreign tourists’ arrivals and travel revenues.

Uncertainty at the start of the pandemic has led to currency depreciation, an increase in sovereign spreads and capital outflows from the region but monetary and financial easing in advanced economies contained financial stress and stabilized international markets. High-frequency fund flow data show that outflows from CESEE were mainly concentrated in the second half of March 2020 and that bond flows were far more strongly affected than equity flows. After this short episode, net fund flows hovered around zero until early October 2020. This is also underlined by more comprehensive quarterly financial accounts data. Financial account outflows spiked in the first quarter of 2020 in many countries and retreated again in the second quarter. Besides portfolio outflows, it was especially outflows from other investments that fueled this development. Among the countries of the region, only Russia continued to report a notable capital outflow also in the second quarter of 2020, mainly on account of stubbornly high portfolio outflows.

As the pressure on financial markets eased, also most CESEE currencies made up parts of their earlier losses between April and August 2020. The reacceleration of COVID-19 infections in recent weeks and/or numerous geopolitical concerns (e.g. unrest in Belarus, the poisoning of Russian opposition leader Alexei Navalny, the latest escalation of the Nagorno-Karabakh conflict, disputes around gas sources in the eastern Mediterranean), however, again weighed on currencies from August 2020. Especially the Hungarian forint, the Russian ruble and the Turkish lira lost in external value.

In Hungary, this coincided with a selective tightening of monetary policy in September 2020, as the central bank raised its one-week deposit rate and its rate on three- and five-year covered loan tenders by 15 basis points to 0.75%.

After the Turkish central bank (TCMB) significantly loosened its monetary policy until June 2020 (see above), it discontinued its repo rate cuts from June onward, mainly because of stubbornly high inflationary pressures. In response to the nearly 7% depreciation of the lira against the euro in August alone, the TCMB progressively tightened monetary policy by canceling its one-week repo auctions and forcing banks to borrow at competitive one-month auctions or via the more expensive overnight markets. However, it left the repo rate unchanged at 8.25%. This policy did not stop the depreciation of the lira and the currency traded at historical lows in September 2020. On September 23, the central bank finally hiked its policy rate to 10.25%. The TCMB justified its rate move on the grounds of inflationary pressures caused by fast economic recovery with strong credit momentum and financial market developments. The depreciation of the lira has not halted at the cutoff date, though.

A reacceleration of newly detected COVID-19 infections since September has led to higher risks for general economic developments and the outlook for the CESEE region. Chart 5 shows that COVID-19 infections remained stable and at a rather low level in the CESEE EU member states during spring. Only Russia and Turkey experienced a first spike that more closely resembled the patterns observed throughout Western Europe. Against this background, containment measures were successively relaxed in many countries from mid-April onward.

Since early September, however, a clear upward trend in infections can be observed and numbers have bounced up to historical heights in many parts of CESEE. This has led to a tightening of containment measures in selected countries and an increase in uncertainty (as e.g. evidenced by renewed pressure on exchange rates).

After a collapse of partly historical dimensions in April 2020, retail sales and industrial production rebounded quickly in May and June (see chart 6), reflecting pent-up demand but also improving economic conditions in the region’s main trading partner countries. Retail trade even returned to positive growth in July 2020. A similar pattern was observed for sentiment indicators, with a historic decline in April and a swift recovery afterward. None of the indicators, however, reached the levels observed before the lockdown.

Improvements, however, have stalled in most recent readings of activity as well as sentiment indicators, suggesting that the recovery could be short lived: Industrial production growth failed to accelerate more notably and remained clearly negative in July. The growth of retail sales remained positive but declined somewhat in August 2020. The growth of production in construction has declined since April, as fewer projects were started after the pandemic hit the region and as some countries scaled back infrastructure spending to make room for anti-crisis support. Readings of the Purchasing Managers’ Index (PMI) for Russia and Turkey declined in September. In Russia, the PMI came in at below 50 points, thereby no longer signaling an economic expansion. The Economic Sentiment Indicator for the CESEE EU member states continued to improve throughout the past months, but it remained notably below its long-term average and improvements have successively become smaller. The beginning second wave will without any doubt further weigh on sentiment and endanger a quick and comprehensive recovery from the economic damage resulting from the lockdown in spring 2020. For more information on the outlook and risks for GDP growth please consult the Outlook for selected CESEE countries ⁶ in the current issue of Focus on European Economic Integration.

2 Slovakia: coronavirus knocked down an already slowing economy

Coronavirus began to cast dark clouds on the economy in late March after it had spread across Europe, including Slovakia. To slow down the spread of the virus, Slovakia, like the rest of Europe, imposed a broad lockdown of the economy in spring. Hence, while private consumption growth took a significant hit, it was still positive in the first quarter of 2020, partially benefiting from households’ stockpiling of food and medicines. In the second quarter, in contrast, household consumption saw a record contraction, a slump in consumer confidence and weakening household income. The decline of fixed investment accelerated in the second quarter, especially in the automotive industry, for various reasons, ranging from firms’ depressed ­liquidity to elevated uncertainty. The worldwide containment measures hit the car industry particularly hard and brought about a massive contraction of exports. Nonetheless, as imports shrank at a similar rate, the contribution of net exports to growth in the second quarter of 2020 was broadly neutral. It is worth mentioning that the automotive industry, which accounts for about 12% of Slovak GDP, took the largest hit from falling exports, but has recovered fast since the relaxation of containment measures in early summer.

The plunge in economic activity has sparked a corresponding reaction in the labor market, which had shown signs of overheating before the crisis hit. The unemployment rate increased from 5.6% in December 2019 to 6.8% in August 2020. A stronger hike in unemployment has been avoided by the introduction of a furlough scheme by the government. Deteriorating labor market conditions have been mirrored by weakening wage growth, which started to show already at the beginning of the year. Wage growth was impaired by a combination of factors such as firm closures and more people on sick or care leave, which also led to a massive decline in the number of hours worked. However, the latter recovered to nearly pre-crisis levels in early summer as economic activity started to normalize. Headline inflation came down from 3.2% in December 2019 to 1.4% in August 2020, owing to lower price rises of food and several services as well as due to declining prices of transportation and energy. The government introduced fiscal measures to counteract the crisis amounting to more than EUR 2 billion (about 2.3% of 2019 GDP). These include wage compensations, rental subsidies and moratoria, higher medical spending, enhanced unemployment, sickness and nursing benefits as well as deferral or waiver of health insurance and social security contributions, some taxes or loan ­repayments. In addition, several state guarantee schemes (worth up to EUR 4 billion) were adopted. As a result, the general government fiscal deficit is now expected to rise to 6% of GDP in 2020, compared to the December 2019 estimate of 1.6% of GDP, and general government debt is projected to go up to roughly 63% this year. As to monetary policy, Národná banka Slovenska (NBS) has adopted a highly accommodative monetary stance. Apart from the measures it implemented in its role as Eurosystem member, the central bank lowered the countercyclical capital buffer rate from 1.5 to 1.0% as of August 1, 2020, revoking its previous decision to increase it to 2.0%. Moreover, the NBS reduced the capital buffer for systemically important banks for Postova Banka from 1% to 0.25%, effective from January 1, 2021.

Table 2: Main economic indicators: Slovakia  

	2017	2018	2019	Q1 19	Q2 19	Q3 19	Q4 19	Q1 20	Q2 20
	Year-on-year change of the period total in %
GDP at constant prices	3.0	3.9	2.4	3.7	2.5	1.5	2.1	–3.7	–12.1
Private consumption	4.5	4.1	2.1	1.3	3.1	1.9	2.3	1.1	–4.0
Public consumption	1.0	0.2	4.6	3.5	6.0	4.2	4.7	1.1	–10.4
Gross fixed capital formation	3.5	2.6	6.8	3.1	4.2	10.4	8.3	–4.8	–14.6
Exports of goods and services	3.6	5.3	1.7	9.0	–0.9	–0.1	–0.5	–6.8	–26.8
Imports of goods and services	3.9	4.9	2.6	6.5	1.4	3.3	–0.5	–1.5	–27.0
	Contribution to GDP growth in percentage points
Domestic demand	3.2	3.4	3.1	1.1	4.6	4.5	2.1	1.9	–11.9
Net exports of goods and services	–0.2	0.5	–0.7	2.6	–2.2	–3.0	0.0	–5.4	–0.2
Exports of goods and services	3.4	5.0	1.7	8.9	–0.9	–0.1	–0.5	–7.0	–24.6
Imports of goods and services	–3.5	–4.6	–2.4	–6.3	–1.3	–2.9	0.5	1.5	24.4
	Year-on-year change of the period average in %
Unit labor costs in the whole economy (nominal, per person)	4.5	3.9	5.9	4.7	7.9	6.5	4.6	8.9	6.6
Unit labor costs in manufacturing (nominal, per hour)	6.5	3.5	5.7	1.7	4.3	7.7	8.7	8.6	20.8
Labor productivity in manufacturing (real, per hour)	1.0	4.7	1.3	7.4	2.6	–2.4	–2.0	–0.7	–11.7
Labor costs in manufacturing (nominal, per hour)	7.5	8.4	6.9	9.2	7.1	5.0	6.5	7.9	6.8
Producer price index (PPI) in industry	2.5	2.4	1.8	2.7	2.9	1.1	0.7	1.7	–1.4
Consumer price index (here: HICP)	1.4	2.5	2.8	2.4	2.6	3.0	3.1	2.9	2.0
	Period average levels
Unemployment rate (ILO definition, %, 15–64 years)	8.2	6.6	5.8	5.9	5.8	5.9	5.7	6.0	6.7
Employment rate (%, 15–64 years)	66.2	67.6	68.4	68.6	68.1	68.5	68.5	68.0	66.8
Key interest rate per annum (%)	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0
	Nominal year-on-year change in the period-end stock in %
Loans to the domestic nonbank private sector1	10.2	8.4	8.4	7.5	6.2	6.8	6.8	6.2	5.6
of which: loans to households	11.8	11.3	11.3	9.5	8.5	8.1	8.0	7.9	7.0
loans to nonbank corporations	7.6	3.4	3.4	3.9	2.1	4.4	4.4	3.0	3.0
	%
Share of foreign currency loans in total loans to the nonbank private sector	0.2	0.1	0.1	0.2	0.1	0.1	0.1	0.3	0.3
Return on assets (banking sector)	0.8	0.8	0.8	0.8	0.9	0.8	0.8	0.3	0.3
Tier 1 capital ratio (banking sector)	16.6	16.6	16.6	16.7	16.8	16.6	16.6	17.3	18.0
NPL ratio (banking sector)	3.6	3.0	2.8	2.9	2.8	2.8	2.8	2.8	2.7
	% of GDP
General government revenues	40.5	40.7	41.5	..	..	..	..	..	..
General government expenditures	41.5	41.8	42.8	..	..	..	..	..	..
General government balance	–1.0	–1.0	–1.3	..	..	..	..	..	..
Primary balance	0.4	0.2	–0.1	..	..	..	..	..	..
Gross public debt	51.3	49.4	48.0	..	..	..	..	..	..
	% of GDP
Debt of nonfinancial corporations (nonconsolidated)	60.0	54.6	26.0	..	..	..	..	..	..
Debt of households and NPISHs2 (nonconsolidated)	41.0	42.5	20.2	..	..	..	..	..	..
	% of GDP (based on EUR), period total
Goods balance	0.7	–0.2	–0.8	1.3	–0.8	–3.1	–0.3	–3.4	0.1
Services balance	1.1	1.0	1.1	0.8	1.6	1.6	0.4	1.3	1.3
Primary income	–2.1	–2.0	–2.1	–1.1	–2.3	–2.4	–2.5	–0.7	–2.0
Secondary income	–1.5	–1.4	–1.1	–1.9	–1.3	–1.1	0.0	–1.4	–0.8
Current account balance	–1.9	–2.6	–2.9	–1.0	–2.8	–5.1	–2.4	–4.2	–1.4
Capital account balance	0.1	1.4	1.0	0.2	1.3	0.0	2.4	1.7	0.3
Foreign direct investment (net)3	–2.8	–0.9	–2.2	–0.5	1.0	–2.0	–6.9	–1.6	3.9
	% of GDP (rolling four-quarter GDP, based on EUR), end of period
Gross external debt	108.2	113.7	111.9	110.4	112.3	113.4	111.9	112.5	123.5
Gross official reserves (excluding gold)	2.3	3.8	5.3	4.4	4.8	5.6	5.3	5.5	6.7
	Months of imports of goods and services
Gross official reserves (excluding gold)	0.3	0.5	0.7	0.5	0.6	0.7	0.7	0.7	0.9
	EUR million, period total
GDP at current prices	84,521	89,606	94,171	21,657	23,667	24,597	24,251	21,485	21,200
Source: Bloomberg, European Commission, Eurostat, national statistical offices, national central banks, wiiw, OeNB.
1 Foreign currency component at constant exchange rates.
2 Nonprofit institutions serving households.
3 + = net accumulation of assets larger than net accumulation of liabilities (net outflow of capital).
– = net accumulation of assets smaller than net accumulation of liabilities (net inflow of capital).

3 Slovenia: recession lets budget deficit soar and sends banks’ ­profitability into nosedive

As a result of the pandemic, the general government budget balance turned into a deficit of around 4.7% of GDP during the first half of 2020, compared to a surplus of 0.5% of GDP in the same period of 2019. In late September, parliament adopted changes to the 2020 budget, increasing the deficit target to 9.3% of GDP, as ­opposed to the original target of a surplus of around 1% of GDP. The large deficit is the result of the fiscal impact of the recession and the government measures taken in response. Compared to the original plan, revenues are expected to drop by around 15% while expenditure is set to rise by 30% .

The sharp contraction of economic activity went hand in hand with slowing price pressures, with inflation remaining in negative territory since April 2020. Deflation was primarily driven by energy prices, not least due to the temporary cut in household electricity prices in response to the pandemic. Core inflation has slowed substantially as well on the back of price developments in services and nonenergy industrial goods.

The growth of credit to the private sector has slowed markedly in recent months (from around 5%–6% in early 2020 to 1%–2% in June 2020), with corporate and retail loans having been affected to a similar extent. Presumably both supply and demand factors have been at work. In the retail segment, housing loans have been least affected, while the growth rate of loans for consumption and other purposes even turned negative. Take-up under the debt service moratorium scheme was very limited, covering only 3.1% of the total number of household loans and 5.6% of the total number of corporate loans by the end of June 2020. Slowing credit activity was mirrored in the decrease in the banking sector’s net interest income during the first half of 2020. Net noninterest income fell even more. The deteriorating economic situation resulted in an increase in impairment and provisioning costs. Overall, the banking sector’s net profit fell by two-thirds during the first half of 2020. Nonperforming exposures continued to decline both in absolute terms and as a percentage of total exposures. However, classified claims in arrears for more than 90 days increased, indicating some deterioration in the quality of banks’ credit portfolios.

Table 3: Main economic indicators: Slovenia  

	2017	2018	2019	Q1 19	Q2 19	Q3 19	Q4 19	Q1 20	Q2 20
	Year-on-year change of the period total in %
GDP at constant prices	4.8	4.4	3.2	4.4	3.3	3.1	2.0	–2.4	–13.1
Private consumption	1.9	3.6	4.8	4.8	6.5	5.8	2.3	–6.4	–17.4
Public consumption	0.4	3.0	1.7	2.5	2.4	2.5	–0.3	4.2	–0.9
Gross fixed capital formation	10.2	9.6	5.8	11.9	9.2	4.8	–1.2	–5.4	–16.5
Exports of goods and services	11.1	6.3	4.1	5.0	5.4	4.9	1.1	–0.9	–23.5
Imports of goods and services	10.7	7.2	4.4	4.8	6.0	7.6	–0.3	–1.9	–24.4
	Contribution to GDP growth in percentage points
Domestic demand	3.6	4.5	3.1	3.8	3.2	4.6	0.9	–3.1	–11.6
Net exports of goods and services	1.2	–0.1	0.1	0.6	0.1	–1.5	1.1	0.7	–1.5
Exports of goods and services	8.6	5.2	3.5	4.3	4.6	4.1	0.9	–0.8	–20.0
Imports of goods and services	–7.4	–5.3	–3.4	–3.7	–4.6	–5.7	0.3	1.5	18.5
	Year-on-year change of the period average in %
Unit labor costs in the whole economy (nominal, per person)	1.2	2.8	4.2	3.1	5.6	4.2	3.9	6.9	11.0
Unit labor costs in manufacturing (nominal, per hour)	–2.4	–2.6	0.0	1.5	–0.4	–1.9	0.6	2.8	20.7
Labor productivity in manufacturing (real, per hour)	9.2	6.5	4.0	5.3	4.9	3.8	2.1	1.6	–13.9
Labor costs in manufacturing (nominal, per hour)	6.7	3.7	3.9	6.9	4.5	1.8	2.7	4.4	3.9
Producer price index (PPI) in industry	2.2	2.1	0.6	1.1	0.8	0.3	0.4	–0.1	–0.6
Consumer price index (here: HICP)	1.6	1.9	1.7	1.3	1.7	2.1	1.6	1.6	–1.2
	Period average levels
Unemployment rate (ILO definition, %, 15–64 years)	6.7	5.2	4.5	4.9	4.3	4.8	4.0	4.6	5.2
Employment rate (%, 15–64 years)	69.3	71.1	71.9	71.3	72.5	72.1	71.6	71.5	70.0
Key interest rate per annum (%)	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0
	Nominal year-on-year change in the period-end stock in %
Loans to the domestic nonbank private sector1	4.9	1.9	1.9	2.8	3.6	3.9	4.3	5.1	1.3
of which: loans to households	6.8	6.4	6.4	6.3	5.9	5.7	5.8	4.1	1.6
loans to nonbank corporations	3.1	–2.2	–2.2	–0.6	1.4	2.1	2.8	6.1	1.1
	%
Share of foreign currency loans in total loans to the nonbank private sector	2.4	2.0	1.7	1.9	1.8	1.8	1.7	1.6	1.6
Return on assets (banking sector)	1.1	1.3	1.3	1.3	1.8	1.6	1.3	0.6	0.6
Tier 1 capital ratio (banking sector)	17.7	17.6	17.8	17.6	17.6	17.7	17.8	..	..
NPL ratio (banking sector)	3.7	2.3	1.1	2.0	1.5	1.5	1.1	1.1	1.2
	% of GDP
General government revenues	44.0	44.3	44.2	..	..	..	..	..	..
General government expenditures	44.1	43.6	43.7	..	..	..	..	..	..
General government balance	0.0	0.7	0.5	..	..	..	..	..	..
Primary balance	2.4	2.7	2.2	..	..	..	..	..	..
Gross public debt	74.1	70.4	66.1	..	..	..	..	..	..
	% of GDP
Debt of nonfinancial corporations (nonconsolidated)	55.4	51.5	24.4	..	..	..	..	..	..
Debt of households and NPISHs2 (nonconsolidated)	27.1	26.9	12.8	..	..	..	..	..	..
	% of GDP (based on EUR), period total
Goods balance	3.7	2.5	2.7	3.7	3.6	1.6	2.2	5.1	5.5
Services balance	5.2	5.8	6.3	5.2	6.1	7.4	6.3	4.9	3.8
Primary income	–2.1	–1.8	–1.4	–1.1	–1.9	–1.6	–1.1	–0.9	–2.0
Secondary income	–0.7	–0.9	–1.0	–1.9	–0.8	–1.0	–0.5	–1.5	–1.2
Current account balance	6.1	5.7	6.5	5.9	7.0	6.3	6.8	7.7	6.0
Capital account balance	–0.8	–0.5	–0.3	–0.2	–0.1	–0.2	–0.9	–0.5	–0.2
Foreign direct investment (net)3	–1.2	–2.0	–1.4	–3.9	–1.1	–1.0	0.0	–1.7	–1.3
	% of GDP (rolling four-quarter GDP, based on EUR), end of period
Gross external debt	100.4	91.8	91.1	91.1	92.5	93.6	91.1	94.7	102.3
Gross official reserves (excluding gold)	1.5	1.5	1.6	1.6	1.7	1.6	1.6	1.7	1.8
	Months of imports of goods and services
Gross official reserves (excluding gold)	0.2	0.2	0.3	0.2	0.3	0.3	0.3	0.3	0.3
	EUR million, period total
GDP at current prices	43,009	45,863	48,393	11,252	12,190	12,489	12,462	11,270	10,828
Source: Bloomberg, European Commission, Eurostat, national statistical offices, national central banks, wiiw, OeNB.
1 Foreign currency component at constant exchange rates.
2 Nonprofit institutions serving households.
3 + = net accumulation of assets larger than net accumulation of liabilities (net outflow of capital).
– = net accumulation of assets smaller than net accumulation of liabilities (net inflow of capital).

4 Bulgaria: severest recession since 1999 amid rising political uncertainty

Due to a sharp fall in external demand and lockdown measures, real GDP dropped by nearly 9% in annual terms in the second quarter of 2020 (the strongest quarterly contraction since 1999). A production-side view reveals that the recession was mainly driven by wholesale and retail trade, transportation, accommodation and industry sectors, while the contribution of information and communication sectors was still positive. HICP inflation fell from 3.1% in February to 0.6% in August 2020, mainly driven by a decline in energy prices. On the other hand, ­Bulgaria’s utilities regulator decided to raise gas prices by 20% as of September 2020 and by another 10% as of October. Compared to the sharp GDP contraction, labor market distortions have been moderate so far, mostly due to government ­support measures. At end-August, the unemployment rate (seasonally adjusted) stood at 6.2% and was thus about 2 percentage points higher than before the crisis.

Rising COVID-19 cases had a severe impact on tourism, which saw a stronger decline than in most other EU countries. Nights spent by nonresidents in Bulgaria were lower by 96% in June and by 78% in July compared to the same period a year ago. Domestic tourism slowed less severely but still substantially. Preliminary data indicate an even steeper annual decline in August as compared to July.

The so-called 60:40 job retention scheme has emerged as one of the main crisis mitigation measures adopted by the government. Under this scheme, the state supported affected businesses by taking over 60% of gross salaries of employees under the condition that employers retain their staff and pay the remaining 40%. The scheme expired in September, and although the government had signaled its willingness to extend it, no decision had been taken at the time of writing. For the particularly hard-hit hospitality industry, an analogous 80:20 scheme with a duration until the end of 2020 was set up, with discussions going on about extending it until May 2021.

Despite the economic policy measures, the consolidated general government budget remained in surplus through the first eight months of the year, partly reflecting a reprioritization of expenditures and some delay in implementing the measures. So far, the government has been successful in issuing long-term bonds at favorable conditions, exploiting in September already half of the annual borrowing amount.

Marking an important milestone, the Bulgarian lev was included in the exchange rate mechanism ERM II on July 10, 2020, with its existing currency board arrangement in place. The latter remains comfortably backed by a comparatively large share of gross official reserves (excluding gold) of more than 43% of GDP. Also, on October 1, Bulgaria joined the SSM, which implies that the ECB started to directly supervise five banks in Bulgaria; three of these banks are the largest banks of the country and the other two are part of important cross-border groups.

Quite in parallel to ERM II accession, mass anti-government protests erupted in early July and persisted until most recently. These protests are rooted in people’s perception of state capture, a lack of judiciary independence and widespread corruption and are calling for a resignation of the government and the chief prosecutor. On a related note, political struggles between the opposition-backed president and the government have intensified.

Table 4: Main economic indicators: Bulgaria  

	2017	2018	2019	Q1 19	Q2 19	Q3 19	Q4 19	Q1 20	Q2 20
	Year-on-year change of the period total in %
GDP at constant prices	3.5	3.1	3.4	4.5	3.6	2.9	2.9	1.2	–8.7
Private consumption	3.8	4.4	5.8	3.8	7.1	7.0	5.3	1.2	–5.8
Public consumption	4.3	5.3	5.5	6.9	1.4	6.1	7.5	2.0	1.1
Gross fixed capital formation	3.2	5.4	2.2	0.2	0.9	0.9	5.6	–7.1	–8.8
Exports of goods and services	5.8	1.7	1.9	4.1	0.3	3.7	–0.3	1.8	–19.6
Imports of goods and services	7.4	5.7	2.4	2.8	1.2	6.3	–0.5	0.3	–18.9
	Contribution to GDP growth in percentage points
Domestic demand	4.2	5.5	3.6	3.5	4.2	4.0	2.8	–0.1	–8.2
Net exports of goods and services	–0.7	–2.4	–0.3	0.8	–0.6	–1.1	0.1	1.1	–0.6
Exports of goods and services	3.7	1.1	1.3	2.9	0.2	2.5	–0.2	1.3	–12.2
Imports of goods and services	–4.4	–3.6	–1.5	–2.1	–0.8	–3.6	0.3	–0.2	11.6
	Year-on-year change of the period average in %
Unit labor costs in the whole economy (nominal, per person)	8.4	6.3	3.0	2.9	4.1	1.5	3.3	4.6	10.0
Unit labor costs in manufacturing (nominal, per hour)	6.0	2.0	6.3	2.5	6.5	8.9	7.6	7.8	9.8
Labor productivity in manufacturing (real, per hour)	6.2	7.7	3.7	10.1	2.9	–0.3	3.3	1.2	0.9
Labor costs in manufacturing (nominal, per hour)	12.6	9.8	10.5	12.9	9.7	8.6	11.1	9.1	10.7
Producer price index (PPI) in industry	4.9	4.0	3.0	3.3	2.7	3.4	2.8	1.4	–4.4
Consumer price index (here: HICP)	1.2	2.6	2.5	2.5	2.8	2.2	2.3	3.0	1.1
EUR per 1 BGN, + = BGN appreciation	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0
	Period average levels
Unemployment rate (ILO definition, %, 15–64 years)	6.3	5.3	4.3	5.1	4.2	3.7	4.1	4.6	6.0
Employment rate (%, 15–64 years)	66.9	67.7	70.1	68.3	70.7	71.4	70.0	68.1	67.4
Key interest rate per annum (%)1	..	..	..	..	..	..	..	..	..
BGN per 1 EUR	2.0	2.0	2.0	2.0	2.0	2.0	2.0	2.0	2.0
	Nominal year-on-year change in the period-end stock in %
Loans to the domestic nonbank private sector2	4.8	8.3	8.3	7.9	6.9	7.2	9.4	9.1	6.6
of which: loans to households	6.1	11.2	11.2	11.0	8.1	9.1	9.5	9.9	8.0
loans to nonbank corporations	4.1	6.6	6.6	6.1	6.2	6.0	9.3	8.7	5.7
	%
Share of foreign currency loans in total loans to the nonbank private sector	37.9	34.9	33.2	34.1	33.5	33.1	33.2	32.7	32.6
Return on assets (banking sector)	1.2	1.7	1.5	1.2	1.7	1.6	1.5	1.0	0.9
Tier 1 capital ratio (banking sector)	20.9	19.4	19.5	18.3	19.7	20.2	19.5	19.8	22.5
NPL ratio (banking sector)	6.9	5.1	4.2	4.9	4.8	5.0	4.2	4.2	5.2
	% of GDP
General government revenues	36.0	38.5	38.4	..	..	..	..	..	..
General government expenditures	34.9	36.6	36.3	..	..	..	..	..	..
General government balance	1.1	2.0	2.1	..	..	..	..	..	..
Primary balance	1.9	2.6	2.7	..	..	..	..	..	..
Gross public debt	25.3	22.3	20.4	..	..	..	..	..	..
	% of GDP
Debt of nonfinancial corporations (nonconsolidated)	85.2	83.2	76.9	..	..	..	..	..	..
Debt of households and NPISHs3 (nonconsolidated)	22.6	23.0	21.3	..	..	..	..	..	..
	% of GDP (based on EUR), period total
Goods balance	–1.5	–3.3	–2.8	–2.7	–4.0	–1.6	–2.9	–3.0	–1.1
Services balance	5.9	6.3	6.2	3.1	5.6	12.1	3.5	5.4	4.2
Primary income	–4.4	–1.2	–2.8	–2.9	–3.2	–3.2	–1.8	–2.9	–2.5
Secondary income	3.5	3.5	3.4	4.3	4.7	2.9	2.0	3.6	1.1
Current account balance	3.5	5.3	4.0	1.8	3.1	10.2	0.7	3.1	1.8
Capital account balance	1.0	1.1	1.5	1.5	1.6	1.6	1.2	1.4	2.0
Foreign direct investment (net)4	–2.5	–0.6	–1.3	–0.7	–0.8	–2.3	–1.2	–2.1	–0.8
	% of GDP (rolling four-quarter GDP, based on EUR), end of period
Gross external debt	71.8	65.9	62.2	65.6	64.5	64.5	62.2	61.2	62.0
Gross official reserves (excluding gold)	42.5	42.1	38.0	41.0	40.1	39.5	38.0	40.3	43.3
	Months of imports of goods and services
Gross official reserves (excluding gold)	8.1	8.1	7.6	7.9	7.9	7.7	7.6	8.1	9.1
	EUR million, period total
GDP at current prices	52,310	56,087	60,675	12,711	15,070	16,184	16,710	13,076	14,007
Source: Bloomberg, European Commission, Eurostat, national statistical offices, national central banks, wiiw, OeNB.
1 Not available in a currency board regime.
2 Foreign currency component at constant exchange rates.
3 Nonprofit institutions serving households.
4 + = net accumulation of assets larger than net accumulation of liabilities (net outflow of capital).
– = net accumulation of assets smaller than net accumulation of liabilities (net inflow of capital).

5 Croatia: exports plummet as spring tourist season falls victim to lockdown

Without a stabilizing monetary policy and substantial government support measures, the slump could have been much worse. Government packages amounted to an estimated 11% of GDP and included mainly state guarantees for loans, tax deferrals and write-offs. Most of direct fiscal spending was for the wage support scheme for enterprises affected by COVID-19. The scheme was recently extended until end-2020, but eligibility criteria were tightened over time. Since the peak in May, the number of workers for which employers received wage support declined from around 550,000 (more than 30% of Croatia’s labor force) to around 57,500 at end-July. In August, the unemployment rate was 8.3%, 1.8 percentage points higher compared to August 2019.

The Croatian central bank (HNB) was very active in the early stages of the ­pandemic, conducting foreign currency interventions and liquidity operations and establishing a swap line with the ECB (agreed until June 2021). Foreign currency interventions led to a temporary decline of international reserves to EUR 15.7 billion in May, but reserves had returned to their end-2019 level of around EUR 18 billion by end-July (approximately 9 months of imports). In April, monthly HICP inflation turned negative and stood at –0.4% in August, largely due to a strong contraction in energy prices. Core inflation also declined but remained positive at 0.5% in August 2020.

The HNB reported that the banking sector’s return on assets in the first half of 2020 halved to 0.76% compared to last year. Four out of twenty banks were ­recording losses. The tier 1 capital ratio stood at a high level of 24% in mid-2020, and the ratio of nonperforming loans (NPL ratio) was 5.5%, both roughly unchanged compared to end-2019. The rise in NPLs was prevented by regulatory easing, but IFRS 9 “stage 2” loans increased strongly. As of June 10, 2020, 8% of the banking sector’s credit volume was covered by a moratorium, according to the HNB. 76% of moratoria were granted to households, while corporates accounted for the bulk of the volume (71% of the total).

The fiscal response to the crisis has led to a sharp increase of the already high level of sovereign debt, which reached 85.3% of GDP in the second quarter of 2020 versus 73.2% of GDP in 2019, and the budget deficit stood at 7.5% of GDP in the first half of 2020. Croatia’s external debt increased to 79.7% of GDP in the second quarter of 2020 from 75.8% at end-2019.

Table 5: Main economic indicators: Croatia  

	2017	2018	2019	Q1 19	Q2 19	Q3 19	Q4 19	Q1 20	Q2 20
	Year-on-year change of the period total in %
GDP at constant prices	3.1	2.7	2.9	4.1	2.4	2.9	2.5	0.4	–15.1
Private consumption	3.1	3.2	3.5	4.3	2.7	3.0	4.0	0.8	–13.8
Public consumption	2.2	1.3	3.3	3.1	3.9	2.9	3.5	4.8	0.7
Gross fixed capital formation	5.1	4.1	7.1	11.5	8.2	5.0	4.0	3.1	–14.7
Exports of goods and services	6.8	3.7	4.6	4.1	3.3	5.1	5.6	–3.0	–40.6
Imports of goods and services	8.4	7.5	4.8	6.5	8.3	4.3	0.1	–5.8	–28.1
	Contribution to GDP growth in percentage points
Domestic demand	3.8	4.5	3.1	6.4	5.2	1.0	0.4	–2.0	–10.6
Net exports of goods and services	–0.6	–1.8	–0.1	–2.1	–2.7	1.6	2.2	2.1	–4.6
Exports of goods and services	3.3	1.8	2.3	1.5	1.6	3.6	2.3	–1.1	–19.8
Imports of goods and services	–3.9	–3.7	–2.5	–3.6	–4.3	–2.0	–0.1	3.2	15.2
	Year-on-year change of the period average in %
Unit labor costs in the whole economy (nominal, per person)	..	..	..	..	..	..	..	..	..
Unit labor costs in manufacturing (nominal, per hour)	1.1	6.5	11.4	8.0	11.3	12.2	14.5	5.4	6.7
Labor productivity in manufacturing (real, per hour)	3.6	2.2	–7.2	–0.1	–9.3	–8.1	–10.3	–5.1	–6.2
Labor costs in manufacturing (nominal, per hour)	4.6	9.0	3.6	7.9	0.9	3.2	2.7	0.0	0.1
Producer price index (PPI) in industry	2.0	2.2	0.8	1.4	1.6	–0.2	0.3	–0.1	–5.4
Consumer price index (here: HICP)	1.3	1.6	0.8	0.8	0.8	0.7	0.9	1.2	–0.4
EUR per 1 HRK, + = HRK appreciation	0.9	0.6	0.0	0.2	–0.3	0.3	–0.3	–0.9	–2.1
	Period average levels
Unemployment rate (ILO definition, %, 15–64 years)	11.3	8.6	6.7	7.6	6.2	5.8	7.3	7.1	6.5
Employment rate (%, 15–64 years)	58.9	60.7	62.1	61.2	61.8	63.0	62.2	61.4	62.2
Key interest rate per annum (%)	..	..	..	..	..	..	..	..	..
HRK per 1 EUR	7.5	7.4	7.4	7.4	7.4	7.4	7.4	7.5	7.6
	Nominal year-on-year change in the period-end stock in %
Loans to the domestic nonbank private sector1	0.6	2.4	2.4	3.5	2.8	2.3	3.4	4.7	2.3
of which: loans to households	2.2	4.7	4.7	5.9	6.0	6.3	6.7	5.3	3.0
loans to nonbank corporations	–1.6	–0.8	–0.8	0.2	–1.6	–3.3	–1.3	3.9	1.2
	%
Share of foreign currency loans in total loans to the nonbank private sector	56.9	54.7	51.5	54.4	53.0	51.9	51.5	51.5	51.4
Return on assets (banking sector)	0.9	1.2	1.4	1.3	1.5	1.4	1.4	1.0	0.8
Tier 1 capital ratio (banking sector)	22.3	22.1	24.0	21.6	22.2	22.0	24.0	22.7	24.0
NPL ratio (banking sector)	8.8	7.6	5.5	7.4	7.3	6.0	5.5	5.4	5.5
	% of GDP
General government revenues	46.1	46.5	47.5	..	..	..	..	..	..
General government expenditures	45.3	46.3	47.1	..	..	..	..	..	..
General government balance	0.8	0.2	0.4	..	..	..	..	..	..
Primary balance	3.5	2.5	2.6	..	..	..	..	..	..
Gross public debt	77.8	74.7	73.2	..	..	..	..	..	..
	% of GDP
Debt of nonfinancial corporations (nonconsolidated)	93.8	92.2	88.0	..	..	..	..	..	..
Debt of households and NPISHs2 (nonconsolidated)	34.2	34.1	32.5	..	..	..	..	..	..
	% of GDP (based on EUR), period total
Goods balance	–17.2	–18.7	–19.4	–21.8	–22.3	–15.8	–18.4	–20.9	–17.1
Services balance	17.9	17.9	19.2	1.9	17.5	43.6	8.2	3.4	4.2
Primary income	–1.4	–1.6	–1.6	–1.5	–2.7	–1.6	–0.6	0.6	0.2
Secondary income	4.2	4.3	4.6	3.8	5.0	3.6	6.0	5.1	6.7
Current account balance	3.5	1.8	2.7	–17.5	–2.6	29.8	–4.8	–11.9	–6.0
Capital account balance	1.1	1.4	2.1	1.7	2.8	1.5	2.4	1.9	3.1
Foreign direct investment (net)3	–2.3	–1.6	–2.0	–4.3	0.6	–2.3	–2.4	–2.8	–1.6
	% of GDP (rolling four-quarter GDP, based on EUR), end of period
Gross external debt	89.0	82.7	75.8	83.7	85.1	80.6	75.8	74.7	79.7
Gross official reserves (excluding gold)	32.0	33.8	34.4	35.0	37.7	38.2	34.4	30.5	33.5
	Months of imports of goods and services
Gross official reserves (excluding gold)	7.8	7.9	7.9	8.1	8.6	8.7	7.9	7.1	8.0
	EUR million, period total
GDP at current prices	49,105	51,631	53,943	11,871	13,542	15,271	13,259	12,045	11,171
Source: Bloomberg, European Commission, Eurostat, national statistical offices, national central banks, wiiw, OeNB.
1 Foreign currency component at constant exchange rates.
2 Nonprofit institutions serving households.
3 + = net accumulation of assets larger than net accumulation of liabilities (net outflow of capital).
– = net accumulation of assets smaller than net accumulation of liabilities (net inflow of capital).

6 Czech Republic: economy in worst doldrums in country’s history

With regard to the balance of payments, the COVID-19 crisis has led to a significantly lower outflow of dividends. As a consequence, the deficit of the primary income balance was unusually low in the six months to June 2020 so that the current account recorded a significant surplus. The originally envisaged general government deficit of CZK 40 billion (0.7% of GDP) for 2020 has been revised three times to currently CZK 500 billion (around 9.3% of GDP). Public debt is projected to rise accordingly, to about 37% of GDP in 2020. Until the outbreak of the crisis, GDP growth was held back by a tight labor market characterized by labor shortages, buoyant wage growth and record low unemployment. As the crisis started to unfold, the unemployment rate rose only modestly from a low of 2% in February to 2.7% in August. A more significant rise in unemployment has been prevented (or delayed) by the government’s job retention scheme as well as the fact that some foreign and older workers pulled out of the labor force. Despite the ­resulting lower pressure on wages and a significant drop in the oil price, inflation (averaging 3.5% in the first eight months of 2020) remains above the central bank’s tolerance band (2% ±1 percentage point). This is due to a weaker koruna, higher food and administered prices as well as increased costs for firms due to supply ­restrictions and new sanitary requirements.

The country’s favorable fiscal position provided the government with ample space to introduce a large set of measures to mitigate the economic damage caused by the pandemic. Hence, a job retention scheme, benefit payments to self-employed, income support to workers caring for children and deferrals of taxes, loan and rent repayments were put in place. In addition, a loan and guarantee program worth 16% of GDP was launched to preserve the liquidity of firms. While a fiscal package totaling more than 20% of GDP is rather generous by international standards, the disbursements recorded so far suggest that actual anti-crisis support is likely to turn out notably lower. The Czech central bank eased its monetary policy in the reporting period by cutting its policy rate by 200 basis points to 0.25% between end-March and end-May. Moreover, the central bank further reduced the countercyclical capital buffer, broadened the range of eligible collateral, introduced liquidity-­providing operations with longer maturities and relaxed regulatory limits for mortgages.

Table 6: Main economic indicators: Czech Republic  

	2017	2018	2019	Q1 19	Q2 19	Q3 19	Q4 19	Q1 20	Q2 20
	Year-on-year change of the period total in %
GDP at constant prices	5.2	3.2	2.3	2.5	2.1	3.0	1.7	–1.6	–10.8
Private consumption	4.0	3.5	3.1	2.8	3.2	3.3	3.0	0.0	–7.3
Public consumption	1.8	3.8	2.3	1.9	2.7	3.2	1.5	4.4	1.8
Gross fixed capital formation	4.9	10.0	2.2	2.8	–0.3	1.9	4.0	–3.8	–4.6
Exports of goods and services	7.2	3.7	1.3	1.1	1.8	4.3	–1.7	–1.5	–23.1
Imports of goods and services	6.3	5.8	1.4	1.9	0.7	2.2	0.7	–1.3	–18.4
	Contribution to GDP growth in percentage points
Domestic demand	3.9	4.4	2.3	3.1	1.3	1.4	3.4	–1.3	–5.7
Net exports of goods and services	1.2	–1.2	0.0	–0.5	0.9	1.6	–1.8	–0.3	–5.1
Exports of goods and services	5.7	2.9	1.0	0.9	1.4	3.1	–1.3	–1.2	–17.4
Imports of goods and services	–4.5	–4.1	–1.0	–1.4	–0.5	–1.5	–0.5	0.9	12.4
	Year-on-year change of the period average in %
Unit labor costs in the whole economy (nominal, per person)	3.5	6.2	4.1	4.6	4.7	3.1	4.2	5.7	9.4
Unit labor costs in manufacturing (nominal, per hour)	1.4	4.7	7.7	8.2	7.6	6.8	8.1	3.2	16.0
Labor productivity in manufacturing (real, per hour)	6.5	3.9	–0.8	–1.0	–0.7	0.1	–1.7	3.6	–8.3
Labor costs in manufacturing (nominal, per hour)	8.0	8.8	6.8	7.1	6.8	6.8	6.3	6.8	6.3
Producer price index (PPI) in industry	0.8	0.7	1.7	3.1	2.5	1.2	0.1	0.1	1.0
Consumer price index (here: HICP)	2.4	2.0	2.6	2.3	2.4	2.6	3.0	3.7	3.3
EUR per 1 CZK, + = CZK appreciation	2.7	2.7	–0.1	–1.1	–0.3	–0.1	1.1	0.3	–5.1
	Period average levels
Unemployment rate (ILO definition, %, 15–64 years)	2.9	2.3	2.1	2.1	1.9	2.2	2.1	2.0	2.4
Employment rate (%, 15–64 years)	73.6	74.8	75.1	75.0	75.0	75.2	75.3	74.8	74.1
Key interest rate per annum (%)	0.2	1.1	1.9	1.8	1.9	2.0	2.0	2.0	0.6
CZK per 1 EUR	26.3	25.6	25.7	25.7	25.7	25.7	25.6	25.6	27.1
	Nominal year-on-year change in the period-end stock in %
Loans to the domestic nonbank private sector1	6.9	6.8	6.8	5.4	5.3	3.9	5.0	5.6	3.7
of which: loans to households	7.5	7.5	7.5	7.0	6.6	6.3	6.1	6.3	6.1
loans to nonbank corporations	6.2	5.8	5.8	3.6	3.9	1.2	3.8	4.8	0.7
	%
Share of foreign currency loans in total loans to the nonbank private sector	13.3	14.1	14.5	14.9	14.8	15.3	14.5	16.9	16.1
Return on assets (banking sector)	1.1	1.1	1.2	1.0	1.2	1.2	1.2	0.7	0.7
Tier 1 capital ratio (banking sector)	18.7	19.1	20.8	19.1	19.8	19.8	20.8	20.9	22.5
NPL ratio (banking sector)	4.1	3.1	2.4	3.0	2.7	2.5	2.4	2.3	2.4
	% of GDP
General government revenues	41.0	42.2	42.1	..	..	..	..	..	..
General government expenditures	39.5	41.2	41.9	..	..	..	..	..	..
General government balance	1.5	0.9	0.3	..	..	..	..	..	..
Primary balance	2.2	1.8	0.9	..	..	..	..	..	..
Gross public debt	34.7	32.6	30.8	..	..	..	..	..	..
	% of GDP
Debt of nonfinancial corporations (nonconsolidated)	57.4	55.9	53.3	..	..	..	..	..	..
Debt of households and NPISHs2 (nonconsolidated)	32.2	31.6	30.1	..	..	..	..	..	..
	% of GDP (based on EUR), period total
Goods balance	5.0	3.7	4.2	5.5	5.5	3.4	2.4	4.7	2.4
Services balance	2.5	2.3	1.8	2.6	2.6	1.4	0.8	2.7	2.1
Primary income	–5.0	–4.8	–5.6	–3.1	–6.2	–8.2	–4.8	–0.3	–3.2
Secondary income	–0.9	–0.7	–0.7	–2.0	–0.1	–0.9	0.0	–1.6	–0.8
Current account balance	1.6	0.4	–0.4	3.0	1.8	–4.3	–1.5	5.5	0.6
Capital account balance	0.8	0.3	0.2	–0.5	0.6	0.1	0.7	1.4	1.6
Foreign direct investment (net)3	–0.9	–0.9	–1.1	–0.3	–2.0	–1.8	–0.1	0.0	–3.3
	% of GDP (rolling four-quarter GDP, based on EUR), end of period
Gross external debt	88.0	81.4	77.0	79.8	79.1	78.2	77.0	72.8	75.3
Gross official reserves (excluding gold)	63.3	58.9	59.4	59.5	59.4	59.8	59.4	58.6	61.7
	Months of imports of goods and services
Gross official reserves (excluding gold)	10.6	10.0	10.5	10.1	10.2	10.4	10.5	10.6	11.4
	EUR million, period total
GDP at current prices	194,418	210,846	223,955	51,705	56,097	57,132	59,021	52,808	49,438
Source: Bloomberg, European Commission, Eurostat, national statistical offices, national central banks, wiiw, OeNB.
1 Foreign currency component at constant exchange rates.
2 Nonprofit institutions serving households.
3 + = net accumulation of assets larger than net accumulation of liabilities (net outflow of capital).
– = net accumulation of assets smaller than net accumulation of liabilities (net inflow of capital).

7 Hungary: despite deep recession inflation among the highest in the EU

According to preliminary data, the budget showed a deficit of 5.1% of GDP in the year up to mid-2020 (compared to a deficit of 1.3% in the same period of 2019). Given these unfavorable developments, the finance ministry now expects the budget deficit to soar to a level of 7% to 9% of GDP in 2020 (compared to a forecast level of 3.8% to 4.0% in the spring).

After temporarily retreating in the second quarter, inflation reaccelerated to around 4% in July and August, the highest rate in the EU. Core inflation (excluding unprocessed food and energy prices) picked up as well to just above the 3% ±1 percentage point target range set by Magyar Nemzeti Bank (MNB). Notwithstanding the acceleration of inflation, the MNB strived to sustain credit to the economy by expanding its various funding programs. Also, in June and July, it lowered its base rate from 0.9% to 0.6%. It also relaxed provisioning rules in July, and in September, the government decided to prolong the debt service moratorium for vulnerable clients until mid-2021 (as of September 2020, the moratorium, which was implemented as an opt-out scheme, covered 40% to 50% of loans to the private sector). Despite these efforts, credit growth to the corporate sector faltered between March and July 2020. By contrast, the growth rate of credit to households remained roughly unchanged during the same period, as the expansion of highly preferential “baby loans” more than compensated for the slowdown in loans for housing and other purposes.

Amid a fresh wave of forint weakness, the MNB decided in September to reimpose fines for banks’ breaches of their mandatory reserve requirements and their obligation to pay no interest or its effective O/N deposit rate (currently at –0.05%), whichever is lower, on banks’ excess reserves on their reserve accounts. Furthermore, to ease tensions on the foreign currency market, it relaunched short-term weekly foreign currency swaps, supplying euro to banks. For the refinancing of these swaps, the MNB can resort to its foreign currency swap and repo arrangements concluded with major central banks (including the ECB and the BIS) earlier in 2020 in the magnitude of around EUR 10 billion. With effect of October 1, 2020, the MNB also took back the tightening of its foreign exchange funding adequacy ratio and foreign exchange coverage ratio, thus easing banks’ access to foreign exchange funding. As these measures did not yield sufficient results, the MNB raised the ­interest rate at its one-week deposit and three- and five-year covered loan tenders by 15 basis points to 0.75% in late September.

Table 7: Main economic indicators: Hungary  

	2017	2018	2019	Q1 19	Q2 19	Q3 19	Q4 19	Q1 20	Q2 20
	Year-on-year change of the period total in %
GDP at constant prices	4.3	5.1	4.9	5.3	4.9	5.0	4.5	2.2	–13.6
Private consumption	4.7	4.8	5.1	5.0	5.0	4.8	5.3	4.9	–8.1
Public consumption	2.4	0.9	1.7	0.3	0.5	1.3	4.6	1.7	–2.7
Gross fixed capital formation	18.7	17.1	15.3	24.9	17.8	16.1	7.0	–2.6	–13.5
Exports of goods and services	6.9	4.3	6.0	7.3	3.7	10.2	3.3	–0.5	–24.0
Imports of goods and services	8.2	6.8	6.9	7.1	4.6	10.2	5.9	1.3	–15.8
	Contribution to GDP growth in percentage points
Domestic demand	4.8	6.7	5.4	4.9	5.4	4.7	6.4	3.8	–5.8
Net exports of goods and services	–0.5	–1.7	–0.4	0.5	–0.5	0.3	–1.9	–1.6	–7.7
Exports of goods and services	6.0	3.8	5.1	6.6	3.3	8.2	2.7	–0.5	–20.3
Imports of goods and services	–6.4	–5.4	–5.6	–6.1	–3.7	–7.9	–4.6	–1.1	12.6
	Year-on-year change of the period average in %
Unit labor costs in the whole economy (nominal, per person)	4.5	3.5	6.0	5.5	7.5	5.6	5.6	4.4	15.1
Unit labor costs in manufacturing (nominal, per hour)	5.4	7.3	6.4	7.0	8.9	3.6	6.3	5.6	25.7
Labor productivity in manufacturing (real, per hour)	2.5	1.6	4.2	5.0	2.5	6.7	2.9	2.9	–12.0
Labor costs in manufacturing (nominal, per hour)	8.0	9.0	10.9	12.4	11.6	10.6	9.4	8.7	10.5
Producer price index (PPI) in industry	3.3	5.6	2.2	3.2	2.3	1.2	2.1	4.1	2.8
Consumer price index (here: HICP)	2.4	2.9	3.4	3.2	3.8	3.1	3.5	4.4	2.5
EUR per 1 HUF, + = HUF appreciation	0.7	–3.0	–2.0	–2.1	–1.8	–1.2	–2.7	–6.3	–8.2
	Period average levels
Unemployment rate (ILO definition, %, 15–64 years)	4.2	3.8	3.5	3.6	3.4	3.5	3.4	3.8	4.7
Employment rate (%, 15–64 years)	68.2	69.3	70.1	69.9	70.0	70.3	70.3	69.7	68.7
Key interest rate per annum (%)	0.9	0.9	0.9	0.9	0.9	0.9	0.9	0.9	0.9
HUF per 1 EUR	309.3	318.8	325.2	317.9	322.9	328.2	331.9	339.1	351.7
	Nominal year-on-year change in the period-end stock in %
Loans to the domestic nonbank private sector1	4.3	9.9	9.9	11.0	12.1	12.2	12.4	15.3	11.1
of which: loans to households	1.3	5.8	5.8	7.7	7.6	12.7	15.4	18.0	18.5
loans to nonbank corporations	6.8	13.1	13.1	13.5	15.4	11.8	10.3	13.5	6.2
	%
Share of foreign currency loans in total loans to the nonbank private sector	23.5	24.0	23.8	23.8	24.1	24.0	23.8	25.6	24.4
Return on assets (banking sector)	1.8	1.4	1.2	1.4	1.3	1.3	1.2	0.2	0.3
Tier 1 capital ratio (banking sector)	21.1	17.8	16.4	16.3	16.8	15.8	16.4	15.6	15.8
NPL ratio (banking sector)	3.7	2.2	2.6	3.4	3.1	3.0	2.6	2.5	2.9
	% of GDP
General government revenues	44.5	44.5	44.0	..	..	..	..	..	..
General government expenditures	47.0	46.7	46.1	..	..	..	..	..	..
General government balance	–2.5	–2.1	–2.0	..	..	..	..	..	..
Primary balance	0.2	0.2	0.2	..	..	..	..	..	..
Gross public debt	72.9	70.2	66.3	..	..	..	..	..	..
	% of GDP
Debt of nonfinancial corporations (nonconsolidated)	65.7	65.4	59.1	..	..	..	..	..	..
Debt of households and NPISHs2 (nonconsolidated)	18.5	17.6	15.9	..	..	..	..	..	..
	% of GDP (based on EUR), period total
Goods balance	1.4	–1.3	–2.1	–0.7	–1.0	–3.3	–3.0	–0.6	–2.6
Services balance	5.5	5.8	5.3	5.0	5.9	6.0	4.1	4.5	2.1
Primary income	–4.0	–3.7	–2.7	–2.3	–3.6	–2.5	–2.4	–1.7	–1.6
Secondary income	–0.9	–0.5	–0.7	–1.6	–0.1	–1.1	–0.2	–1.2	–0.8
Current account balance	2.0	0.3	–0.3	0.5	1.2	–0.9	–1.6	1.0	–2.8
Capital account balance	0.9	2.2	1.8	1.0	1.3	1.3	3.5	1.8	2.2
Foreign direct investment (net)3	–1.6	–2.0	0.1	–1.3	2.2	0.6	–1.2	–1.8	–0.9
	% of GDP (rolling four-quarter GDP, based on EUR), end of period
Gross external debt	84.1	80.8	73.6	82.3	81.6	78.0	73.6	71.8	77.8
Gross official reserves (excluding gold)	18.5	19.7	18.8	19.3	18.6	19.1	18.8	16.9	20.7
	Months of imports of goods and services
Gross official reserves (excluding gold)	2.8	2.9	2.8	2.9	2.8	2.8	2.8	2.5	3.2
	EUR million, period total
GDP at current prices	125,575	133,661	143,701	32,093	35,854	36,706	39,049	31,876	30,294
Source: Bloomberg, European Commission, Eurostat, national statistical offices, national central banks, wiiw, OeNB.
1 Foreign currency component at constant exchange rates.
2 Nonprofit institutions serving households.
3 + = net accumulation of assets larger than net accumulation of liabilities (net outflow of capital).
– = net accumulation of assets smaller than net accumulation of liabilities (net inflow of capital).

8 Poland: comprehensive policy response as monetary policy focuses on the medium term

In the first half-year of 2020, given the fall in labor productivity, annual growth of nominal ULC in manufacturing accelerated in both Poland and the euro area and reached double-digit levels in mid-2020. The slightly higher ULC rise in Poland was more than offset by the 6% depreciation of the złoty to 4.50 per euro from February to April 2020. The złoty remained close to this value until October 2020. Annual headline inflation declined from a peak of 4.1% (HICP) and 4.7% (national CPI) in February to 3.7% and 2.9% (CPI), respectively, in August 2020. By contrast, core inflation increased due to services prices from 3.6% in February 2020 (both HICP excluding energy and unprocessed food and CPI excluding energy and all food) to 4.6% and 4.0% (core CPI), respectively, in August 2020.

On May 29, 2020, the Monetary Policy Council (MPC), pursuing an inflation target of 2.5% ± 1 percentage point (CPI), continued its comprehensive easing measures of March and April by cutting the main policy rate further to 0.1% from 0.5%. At the same time, it cut the Lombard rate to 0.5% from 1.0%, but maintained its deposit rate at 0.0%, preferring an asymmetric band to negative rates. On October 7, 2020, the MPC declared to continue its outright purchases of government(-guaranteed) debt securities in the secondary market to ensure the liquidity of these markets and to strengthen the monetary transmission mechanism. Moreover, the MPC declared that it would offer bill discount credit aimed at refinancing loans granted to enterprises by banks. In parallel, commercial banks’ moratoria options to households and SMEs were prolonged.

Regarding fiscal policy, Polish authorities expect the headline deficit to rise to about 12% of GDP in 2020 (from 0.7% in 2019) and to decline to about 6% of GDP in 2021. General government gross debt is projected to rise to 62% of GDP in 2020 (from 46% at the end of 2019) and further to 64% of GDP at the end of 2021. Recently, Poland received EU support to mitigate unemployment risk during an emergency (SURE) of about EUR 11 billion, which might partly finance the job protection component (amounting to EUR 7 billion) of the March economic ­support package (EUR 46 billion, 8.5% of GDP).

Table 8: Main economic indicators: Poland  

	2017	2018	2019	Q1 19	Q2 19	Q3 19	Q4 19	Q1 20	Q2 20
	Year-on-year change of the period total in %
GDP at constant prices	4.9	5.3	4.1	4.9	4.2	4.3	3.4	1.7	–7.9
Private consumption	4.5	4.5	3.8	3.7	4.0	3.9	3.6	0.8	–11.0
Public consumption	2.9	3.7	4.9	7.5	3.9	5.7	3.3	3.9	4.3
Gross fixed capital formation	4.0	9.4	7.2	12.0	9.3	4.1	5.9	0.8	–11.1
Exports of goods and services	9.5	7.0	4.7	8.5	3.6	5.0	1.9	0.6	–14.3
Imports of goods and services	9.8	7.6	2.7	5.9	4.0	3.2	–2.1	–0.1	–18.2
	Contribution to GDP growth in percentage points
Domestic demand	4.7	5.4	2.9	3.2	4.2	3.2	1.3	1.2	–9.2
Net exports of goods and services	0.3	0.0	1.2	1.7	–0.1	1.1	2.0	0.4	1.3
Exports of goods and services	5.0	3.8	2.6	4.9	2.1	2.8	1.0	0.4	–8.2
Imports of goods and services	–4.7	–3.8	–1.4	–3.2	–2.1	–1.7	1.0	0.0	9.5
	Year-on-year change of the period average in %
Unit labor costs in the whole economy (nominal, per person)	2.1	3.1	3.1	2.9	2.3	3.4	3.9	5.9	11.5
Unit labor costs in manufacturing (nominal, per hour)	2.8	4.7	4.2	2.5	4.7	5.5	4.3	6.3	15.3
Labor productivity in manufacturing (real, per hour)	3.5	3.1	2.4	3.5	2.4	1.7	2.2	2.1	–7.8
Labor costs in manufacturing (nominal, per hour)	6.4	8.0	6.8	6.1	7.2	7.3	6.6	8.5	6.3
Producer price index (PPI) in industry	2.7	2.1	1.3	2.6	1.6	0.8	0.3	0.3	–1.2
Consumer price index (here: HICP)	1.6	1.2	2.1	1.2	2.2	2.5	2.6	3.9	3.4
EUR per 1 PLN, + = PLN appreciation	2.5	–0.1	–0.9	–2.9	–0.5	–0.4	0.3	–0.5	–4.9
	Period average levels
Unemployment rate (ILO definition, %, 15–64 years)	5.0	3.9	3.4	4.0	3.3	3.2	2.9	3.2	3.2
Employment rate (%, 15–64 years)	66.1	67.4	68.2	67.2	68.2	68.9	68.5	68.4	67.9
Key interest rate per annum (%)	1.5	1.5	1.5	1.5	1.5	1.5	1.5	1.4	0.4
PLN per 1 EUR	4.3	4.3	4.3	4.3	4.3	4.3	4.3	4.3	4.5
	Nominal year-on-year change in the period-end stock in %
Loans to the domestic nonbank private sector1	6.2	6.4	6.4	6.9	6.7	6.6	5.0	4.7	1.5
of which: loans to households	4.8	5.6	5.6	5.6	5.9	6.1	5.6	5.1	2.9
loans to nonbank corporations	8.7	7.6	7.6	9.2	8.2	7.3	4.1	4.1	–0.9
	%
Share of foreign currency loans in total loans to the nonbank private sector	21.3	20.8	19.2	20.6	19.8	20.0	19.2	20.2	19.8
Return on assets (banking sector)	0.8	0.7	0.7	0.6	0.8	0.8	0.7	0.3	0.3
Tier 1 capital ratio (banking sector)	17.2	17.1	17.0	17.0	16.9	17.0	17.0	16.3	17.9
NPL ratio (banking sector)	6.8	6.8	6.6	6.8	6.8	6.8	6.6	6.6	6.9
	% of GDP
General government revenues	39.8	41.3	41.3	..	..	..	..	..	..
General government expenditures	41.2	41.5	42.0	..	..	..	..	..	..
General government balance	–1.5	–0.2	–0.7	..	..	..	..	..	..
Primary balance	0.2	1.2	0.7	..	..	..	..	..	..
Gross public debt	50.6	48.8	46.0	..	..	..	..	..	..
	% of GDP
Debt of nonfinancial corporations (nonconsolidated)	47.2	45.1	42.8	..	..	..	..	..	..
Debt of households and NPISHs2 (nonconsolidated)	35.6	34.7	33.0	..	..	..	..	..	..
	% of GDP (based on EUR), period total
Goods balance	–0.1	–1.3	0.2	0.1	0.0	–0.1	0.7	0.8	3.3
Services balance	3.8	4.3	4.5	4.7	4.6	4.5	4.1	4.9	4.4
Primary income	–4.0	–4.0	–3.9	–2.6	–4.3	–4.6	–3.8	–1.5	–2.5
Secondary income	0.0	–0.3	–0.3	–0.9	–0.2	–0.3	–0.1	–0.6	0.5
Current account balance	–0.3	–1.3	0.5	1.3	0.2	–0.5	1.0	3.6	5.6
Capital account balance	1.3	2.1	2.0	0.7	2.2	1.9	3.0	1.8	3.0
Foreign direct investment (net)3	–1.4	–2.6	–1.6	–4.8	0.5	–2.6	0.0	–3.6	–0.5
	% of GDP (rolling four-quarter GDP, based on EUR), end of period
Gross external debt	68.4	63.7	59.7	62.3	61.6	60.7	59.7	56.4	57.1
Gross official reserves (excluding gold)	19.5	19.6	19.8	19.1	18.5	19.4	19.8	18.6	19.7
	Months of imports of goods and services
Gross official reserves (excluding gold)	4.6	4.5	4.6	4.4	4.2	4.5	4.6	4.4	4.9
	EUR million, period total
GDP at current prices	467,607	497,394	529,101	121,284	127,992	131,029	148,797	127,709	116,567
Source: Bloomberg, European Commission, Eurostat, national statistical offices, national central banks, wiiw, OeNB.
1 Foreign currency component at constant exchange rates.
2 Nonprofit institutions serving households.
3 + = net accumulation of assets larger than net accumulation of liabilities (net outflow of capital).
– = net accumulation of assets smaller than net accumulation of liabilities (net inflow of capital).

9 Romania: investments cushion COVID-19-induced economic plunge, while trade deficit widens

Despite the economic contraction, Romania’s trade deficit widened noticeably in the first half of 2020. In the run-up to the crisis, Romania’s unit labor costs in the manufacturing sector had increased markedly. The nominal exchange rate vis-à-vis the euro depreciated only a little in the course of 2020. Yet, the current ­account deficit narrowed slightly, as income balances improved. Better EU fund absorption led to an increase in the capital account and, hence, the net borrowing position from the current and capital accounts declined somewhat. A reduction in intercompany lending caused net FDI outflows in the first quarter of 2020. In the second quarter, modest equity and net FDI inflows combined with a reduction of foreign assets led to positive net FDI inflows again. The bulk of financing in the financial account stemmed from net portfolio inflows, as the government accessed international markets to fund the budget deficit, benefiting from favorable global liquidity conditions. The government estimates the budget deficit to rise to 8.6% of GDP this year. In addition to domestic and international bond issuances, the government can make use of loans in the amount of EUR 4 billion provided under the EU’s SURE instrument, which was designed to tackle sudden increases in public expenditure for the preservation of employment.

To address possible euro liquidity needs during the COVID-19 crisis, the National Bank of Romania (NBR) set up a repo line with the ECB in May. The arrangement was initially planned to remain in place until end-2020 but was prolonged until mid-2021 in August. Under the repo line, the NBR has the possibility to borrow up to EUR 4.5 billion from the ECB in exchange for adequate euro-denominated collateral. Meanwhile, the NBR carried on with its policy response package launched in March 2020 by continuing repo transactions and purchases of leu-­denominated government securities on the secondary market. After a 50-basis point rate cut in March 2020, the NBR further cut its key policy rate in two 25-basis point steps to 1.5%. Consumer price inflation, which is relevant for monetary policy, stood at 2.7% year on year in August and has been relatively close to the mid-point of the NBR’s target band of 2.5% ± 1 percentage point in recent months.

Table 9: Main economic indicators: Romania  

	2017	2018	2019	Q1 19	Q2 19	Q3 19	Q4 19	Q1 20	Q2 20
	Year-on-year change of the period total in %
GDP at constant prices	7.1	4.4	4.1	5.0	4.4	3.0	4.3	2.4	–10.5
Private consumption	9.9	7.2	5.9	7.4	5.1	4.3	7.2	3.8	–13.3
Public consumption	4.5	3.1	7.1	2.4	11.4	2.2	9.4	3.5	4.7
Gross fixed capital formation	3.5	–1.0	17.9	3.2	20.5	25.6	15.7	13.1	1.8
Exports of goods and services	7.8	5.9	3.8	2.9	3.0	3.2	6.2	–1.6	–28.7
Imports of goods and services	10.7	9.2	8.3	11.5	5.5	9.1	7.3	2.2	–21.5
	Contribution to GDP growth in percentage points
Domestic demand	8.5	5.9	5.8	7.4	5.6	5.7	4.8	4.6	–7.9
Net exports of goods and services	–1.4	–1.4	–1.7	–3.5	–1.3	–2.3	–0.3	–2.6	–2.4
Exports of goods and services	3.1	2.6	1.9	2.0	1.4	1.8	2.3	–0.4	–11.9
Imports of goods and services	–4.5	–4.0	–3.6	–5.5	–2.7	–4.1	–2.6	–2.2	9.5
	Year-on-year change of the period average in %
Unit labor costs in the whole economy (nominal, per person)	9.9	9.1	4.5	5.3	3.3	3.5	5.8	6.7	10.4
Unit labor costs in manufacturing (nominal, per hour)	5.6	7.0	12.7	8.0	14.0	14.4	14.4	13.2	27.9
Labor productivity in manufacturing (real, per hour)	8.3	5.5	–0.8	4.1	–1.9	–2.2	–2.6	–2.7	–4.9
Labor costs in manufacturing (nominal, per hour)	14.3	12.8	11.9	12.5	11.9	11.9	11.4	10.2	21.7
Producer price index (PPI) in industry	3.5	5.0	4.0	4.6	4.5	3.5	3.2	2.7	–1.4
Consumer price index (here: HICP)	1.1	4.1	3.9	3.8	4.3	3.9	3.7	3.1	2.1
EUR per 1 RON, + = RON appreciation	–1.7	–1.8	–1.9	–1.7	–2.0	–1.8	–2.2	–1.3	–1.9
	Period average levels
Unemployment rate (ILO definition, %, 15–64 years)	5.1	4.3	4.0	4.2	3.9	4.0	4.0	4.4	5.5
Employment rate (%, 15–64 years)	63.9	64.8	65.8	64.2	66.4	66.7	66.0	65.4	65.2
Key interest rate per annum (%)	1.8	2.4	2.5	2.5	2.5	2.5	2.5	2.4	1.9
RON per 1 EUR	4.6	4.7	4.7	4.7	4.7	4.7	4.8	4.8	4.8
	Nominal year-on-year change in the period-end stock in %
Loans to the domestic nonbank private sector1	4.4	7.9	7.9	6.8	6.4	6.8	5.5	6.2	3.1
of which: loans to households	7.1	9.1	9.1	7.3	6.3	6.6	6.7	7.1	5.3
loans to nonbank corporations	2.5	6.6	6.6	6.3	6.5	7.1	4.2	5.3	0.6
	%
Share of foreign currency loans in total loans to the nonbank private sector	37.2	34.0	32.4	34.2	33.4	33.4	32.4	32.8	32.2
Return on assets (banking sector)	1.3	1.6	1.4	1.6	1.2	1.5	1.4	1.3	1.1
Tier 1 capital ratio (banking sector)	18.0	18.6	20.1	17.9	17.7	17.9	20.1	18.5	20.7
NPL ratio (banking sector)	6.4	5.0	4.1	4.9	4.7	4.6	4.1	3.9	4.4
	% of GDP
General government revenues	30.8	31.9	31.7	..	..	..	..	..	..
General government expenditures	33.5	34.8	36.0	..	..	..	..	..	..
General government balance	–2.6	–2.9	–4.3	..	..	..	..	..	..
Primary balance	–1.4	–1.8	–3.1	..	..	..	..	..	..
Gross public debt	35.1	34.7	35.2	..	..	..	..	..	..
	% of GDP
Debt of nonfinancial corporations (nonconsolidated)	35.1	32.8	29.4	..	..	..	..	..	..
Debt of households and NPISHs2 (nonconsolidated)	15.8	15.8	14.1	..	..	..	..	..	..
	% of GDP (based on EUR), period total
Goods balance	–6.5	–7.2	–7.8	–8.7	–7.7	–7.3	–7.7	–9.7	–9.3
Services balance	4.4	4.1	3.9	4.2	4.4	3.4	3.8	4.9	4.9
Primary income	–1.4	–1.8	–1.4	1.4	–3.2	–2.6	–0.7	1.8	–2.8
Secondary income	0.8	0.6	0.7	0.5	0.1	0.7	1.2	0.9	0.8
Current account balance	–2.8	–4.4	–4.6	–2.6	–6.3	–5.8	–3.3	–2.1	–6.4
Capital account balance	1.2	1.2	1.3	1.6	0.9	0.9	1.7	2.6	1.7
Foreign direct investment (net)3	–2.6	–2.4	–2.4	–2.9	–2.8	–2.8	–1.4	0.9	–3.3
	% of GDP (rolling four-quarter GDP, based on EUR), end of period
Gross external debt	51.9	48.8	47.3	47.7	49.6	49.7	47.3	47.9	50.6
Gross official reserves (excluding gold)	17.8	16.2	14.7	15.3	15.3	16.3	14.7	15.1	15.9
	Months of imports of goods and services
Gross official reserves (excluding gold)	4.8	4.3	4.0	4.1	4.1	4.4	4.0	4.1	4.5
	EUR million, period total
GDP at current prices	187,540	204,637	223,259	42,842	51,618	61,388	67,411	45,022	46,355
Source: Bloomberg, European Commission, Eurostat, national statistical offices, national central banks, wiiw, OeNB.
1 Foreign currency component at constant exchange rates.
2 Nonprofit institutions serving households.
3 + = net accumulation of assets larger than net accumulation of liabilities (net outflow of capital).
– = net accumulation of assets smaller than net accumulation of liabilities (net inflow of capital).

10 Turkey: low level of international reserves increasingly limits space for crisis response

In addition to launching a comprehensive set of liquidity-enhancing measures in March, the Turkish central bank cut its one-week repo rate, the main policy rate, by another 100 basis points on April 22, 2020, and by 50 basis points to 8.25% on May 21. However, in response to year-on-year industrial production and retail sales figures turning positive in July and given continued and sizable lira ­depreciation, the central bank started to tighten liquidity in early August and hiked the policy rate by 200 basis points to 10.25% on September 24, noting inflation expectations containment as the main reason. Between March and October, wage support for short-time work schemes were in place. In April, parliament approved a ban on layoffs until November, which will possibly be extended until mid-2021. On April 25, the Turkish government doubled its COVID-19-related economic support package to 4.4% of GDP, including deferrals of taxes and social insurance payments by six months for all companies in particularly affected industries, support to export companies, benefits for senior citizens and new funds for low-­income families. In early October, the authorities published the actual general government deficit figure of end-August, which was 2.4% of annual GDP.

Table 10: Main economic indicators: Turkey  

	2017	2018	2019	Q1 19	Q2 19	Q3 19	Q4 19	Q1 20	Q2 20
	Year-on-year change of the period total in %
GDP at constant prices	7.5	3.0	0.9	–2.6	–1.7	1.0	6.4	4.4	–9.9
Private consumption	5.9	0.5	1.6	–3.9	–0.5	2.0	8.2	4.0	–8.5
Public consumption	5.0	6.6	4.4	7.3	3.4	6.3	1.6	3.3	–0.8
Gross fixed capital formation	8.3	–0.3	–12.4	–14.2	–20.9	–14.0	0.6	–0.3	–6.1
Exports of goods and services	12.4	9.0	4.9	9.1	6.2	4.7	0.6	0.3	–35.3
Imports of goods and services	10.6	–6.4	–5.3	–29.6	–18.6	3.6	27.8	21.9	–6.4
	Contribution to GDP growth in percentage points
Domestic demand	6.7	1.1	–2.0	–5.5	–6.2	–1.8	5.1	2.8	–6.6
Net exports of goods and services	0.2	3.6	2.3	9.6	5.7	0.5	–5.5	–4.0	–7.5
Exports of goods and services	2.7	2.0	1.2	2.0	1.4	1.2	0.1	0.1	–8.7
Imports of goods and services	–2.5	1.5	1.2	7.6	4.3	–0.7	–5.6	–4.1	1.2
	Year-on-year change of the period average in %
Unit labor costs in the whole economy (nominal, per person)	..	..	..	..	..	..	..	..	..
Unit labor costs in manufacturing (nominal, per hour)	4.0	18.0	22.0	24.7	25.1	22.5	15.7	15.7	13.2
Labor productivity in manufacturing (real, per hour)	6.3	1.7	1.6	–0.4	2.5	0.9	3.4	4.2	13.8
Labor costs in manufacturing (nominal, per hour)	10.5	20.4	23.8	24.2	28.1	23.6	19.7	20.5	28.9
Producer price index (PPI) in industry	15.8	27.0	17.6	30.7	27.9	12.0	4.4	8.9	6.1
Consumer price index (here: HICP)	11.1	16.3	15.2	19.9	18.0	13.5	10.3	12.1	11.7
EUR per 1 TRY, + = TRY appreciation	–18.9	–27.7	–10.4	–23.2	–20.9	4.7	–2.1	–9.4	–12.7
	Period average levels
Unemployment rate (ILO definition, %, 15–64 years)	11.1	11.1	14.0	15.0	13.1	14.3	13.5	13.9	13.1
Employment rate (%, 15–64 years)	51.6	52.0	50.3	49.3	50.7	51.0	50.2	47.6	45.9
Key interest rate per annum (%)	8.0	15.5	20.6	24.0	24.0	20.3	14.3	11.0	8.8
TRY per 1 EUR	4.1	5.7	6.4	6.1	6.6	6.3	6.4	6.7	7.6
	Nominal year-on-year change in the period-end stock in %
Loans to the domestic nonbank private sector	20.7	12.0	11.2	12.9	6.7	–2.2	11.2	15.2	29.1
of which: loans to households	16.3	3.2	15.9	1.5	–0.6	3.7	15.9	23.4	36.4
loans to nonbank corporations	22.3	15.0	9.8	16.6	8.9	–3.8	9.8	12.9	27.0
	%
Share of foreign currency loans in total loans to the ­nonbank private sector	33.0	38.5	35.1	38.6	38.2	35.5	35.1	34.9	31.6
Return on assets (banking sector)	1.6	1.5	1.1	1.2	1.2	1.1	1.1	1.3	1.2
Tier 1 capital ratio (banking sector)	13.6	13.4	13.9	12.6	13.1	13.9	13.9	13.3	14.8
NPL ratio (banking sector)	3.1	4.1	5.7	4.3	4.7	5.3	5.7	5.3	4.7
	% of GDP
General government revenues	31.4	32.3	32.8	..	..	..	..	..	..
General government expenditures	34.1	35.1	35.8	..	..	..	..	..	..
General government balance	–2.8	–2.8	–3.0	..	..	..	..	..	..
Primary balance	–0.6	0.1	0.5	..	..	..	..	..	..
Gross public debt	28.2	30.4	33.1	..	..	..	..	..	..
	% of GDP
Debt of nonfinancial corporations (nonconsolidated)	..	..	..	..	..	..	..	..	..
Debt of households and NPISHs1 (nonconsolidated)	..	..	..	..	..	..	..	..	..
	% of GDP (based on EUR), period total
Goods balance	–6.8	–5.1	–2.2	–1.6	–2.4	–2.1	–2.6	–5.5	–5.7
Services balance	3.0	4.0	4.9	2.6	4.9	7.4	4.1	2.5	–0.4
Primary income	–1.3	–1.5	–1.6	–1.3	–2.2	–1.5	–1.6	–1.3	–1.7
Secondary income	0.3	0.1	0.1	0.1	0.0	0.2	0.2	–0.1	0.0
Current account balance	–4.7	–2.5	1.1	–0.2	0.3	4.0	0.2	–4.5	–7.9
Capital account balance	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0
Foreign direct investment (net)2	–1.0	–1.2	–0.7	–1.2	–0.6	–0.6	–0.6	–1.0	–0.1
	% of GDP (rolling four-quarter GDP, based on EUR), end of period
Gross external debt	50.6	57.3	54.3	60.6	59.5	58.7	54.9	53.5	52.6
Gross official reserves (excluding gold)	9.3	9.6	10.3	10.4	10.3	10.6	10.3	8.1	6.3
	Months of imports of goods and services
Gross official reserves (excluding gold)	3.7	3.7	4.1	4.0	4.0	4.2	4.1	3.2	2.5
	EUR million, period total
GDP at current prices	758,255	662,351	679,154	151,445	155,685	183,630	188,394	159,309	137,692
Source: Bloomberg, European Commission, Eurostat, national statistical offices, national central banks, wiiw, OeNB.
1 Nonprofit institutions serving households.
2 + = net accumulation of assets larger than net accumulation of liabilities (net outflow of capital).
– = net accumulation of assets smaller than net accumulation of liabilities (net inflow of capital).

11 Russia: partial recovery of oil price, sizable fiscal stimulus and strong buffers help the economy to overcome the recession

The Russian currency has so far not declined as much as it had during the crises of 2008–09 and 2014–15. This contributed to reducing the contraction of imports, and, to some degree, stabilizing the banking sector. Overall, from January to ­August 2020, the average exchange rate of the ruble lost about 7% against the U.S. dollar and 6% against the euro (year on year). Given that prior to the coronavirus crisis, consumer price inflation had already been clearly below the 4% target of the Central Bank of Russia (CBR) and given the strong compression of demand due to the lockdown measures, the CBR swiftly switched from its previously restrictive monetary policy stance to an accommodative stance, cutting its key rate in three steps by a total of 175 basis points to 4.25%. In August, inflation stood at 3.6%.

Russia’s federal budget moved into the red in the second quarter of 2020, ­resulting in a deficit of about 2% of GDP in the first six months of the year. However, the shortfall would have been higher by about 2 percentage points of GDP had it not been for the large one-off transfer related to payments received by the CBR from the government for Sberbank shares. Until April 2020, the majority of shares had belonged to the CBR, the transfer was paid out of the National Welfare Fund (NWF). Under the National Plan for Economic Recovery, federal expenditure has been rising strongly since early 2020. A large part of this rise is due to increased health and social spending as well as support for enterprises. Moreover, tax deferrals and benefits have played an important role. The budget shortfall is largely being financed by placement of domestic debt. The NWF’s volume stood at 12% of GDP (at end-August 2020), two-thirds of which made up by liquid assets.

The much lower prices and quantities of oil and gas exports, coupled with the relatively modest depreciation of the ruble, contributed to the sharp contraction of the current account surplus to EUR 20.9 billion from January to August 2020, against EUR 43.5 billion in the corresponding period of 2019. Private net capital outflows rose to EUR 31.2 billion in the first eight months of 2020. Russia’s gross foreign debt slightly declined to EUR 424 billion (as of mid-2020), largely on account of cross-border banking sector deleveraging. Limited foreign exchange sales to support the ruble coupled with exchange rate changes contributed to a modest erosion of the country’s international reserves to EUR 498 billion in late September 2020.

The coronavirus crisis and regulatory lenience is reflected in a still relatively high, but not sharply increasing, NPL ratio (end-June 2020: 17.4%). On a year-on-year basis (until end-June 2020), loans to enterprises continued to grow modestly (+5% in real terms and exchange rate-adjusted), while retail lending was stronger (+12%) but losing momentum, partly due to CBR regulatory restrictions against unsecured consumer credit. As of mid-2020, 7% to 8% of loans had reportedly been restructured.

Table 11: Main economic indicators: Russia  

	2017	2018	2019	Q1 19	Q2 19	Q3 19	Q4 19	Q1 20	Q2 20
	Year-on-year change of the period total in %
GDP at constant prices	1.8	2.5	1.3	0.4	1.1	1.5	2.1	1.6	–8.0
Private consumption	3.7	3.3	2.5	2.6	2.5	2.5	2.5	3.4	–22.1
Public consumption	2.5	1.3	2.2	2.0	2.1	2.3	2.3	1.4	1.6
Gross fixed capital formation	4.7	0.2	1.5	–2.3	5.1	–1.1	2.9	1.8	–11.7
Exports of goods and services	5.0	5.5	–2.3	–0.6	–5.3	–0.8	–2.5	–3.4	0.3
Imports of goods and services	17.3	2.6	3.4	–2.0	–0.2	4.5	10.1	1.1	–22.2
	Contribution to GDP growth in percentage points
Domestic demand	3.9	1.9	2.7	0.2	2.4	2.7	4.9	2.6	–13.4
Net exports of goods and services	–2.3	0.9	–1.4	0.3	–1.4	–1.3	–3.0	–1.2	5.5
Exports of goods and services	1.3	1.5	–0.6	–0.2	–1.5	–0.2	–0.7	–1.0	0.1
Imports of goods and services	–3.6	–0.6	–0.8	0.5	0.1	–1.1	–2.3	–0.3	5.4
	Year-on-year change of the period average in %
Unit labor costs in the whole economy (nominal, per person)	..	..	..	..	..	..	..	..	..
Unit labor costs in manufacturing (nominal, per person)	17.9	1.8	4.5	2.9	6.3	4.2	4.7	7.1	13.4
Labor productivity in manufacturing (real, per person)	7.4	4.9	3.0	3.5	2.2	3.6	2.8	0.8	–8.1
Labor costs in manufacturing (nominal, per person)	26.7	6.6	7.7	6.5	8.6	8.0	7.7	8.0	4.1
Producer price index (PPI) in industry	7.7	12.1	2.3	9.3	6.6	–1.0	–5.7	–2.4	–12.1
Consumer price index (here: CPI)	3.6	3.0	4.6	5.3	5.1	4.4	3.5	2.5	3.2
EUR per 1 RUB, + = RUB appreciation	12.6	–11.0	2.2	–6.6	2.0	6.2	7.7	1.6	–8.9
	Period average levels
Unemployment rate (ILO definition, %, 15–64 years)	5.2	4.8	4.6	4.8	4.5	4.4	4.6	4.7	6.0
Employment rate (%, 15–64 years)	..	..	..	..	..	..	..	..	..
Key interest rate per annum (%)	9.1	7.4	7.3	7.8	7.7	7.3	6.6	6.1	5.5
RUB per 1 EUR	65.9	74.1	72.5	74.9	72.6	71.8	70.5	73.7	79.7
	Nominal year-on-year change in the period-end stock in %
Loans to the domestic nonbank private sector1	5.7	12.3	12.3	11.9	11.6	10.5	10.4	11.1	10.0
of which: loans to households	12.7	22.2	22.2	23.5	22.8	20.7	18.5	17.7	12.5
loans to nonbank corporations	3.1	8.3	8.3	7.2	6.9	6.1	6.7	8.0	8.7
	%
Share of foreign currency loans in total loans to the nonbank private sector	14.7	13.6	11.4	12.2	11.6	11.4	11.4	13.1	11.9
Return on assets (banking sector)	1.0	1.5	2.2	2.5	2.2	2.1	2.2	2.4	1.6
Tier 1 capital ratio (banking sector)	8.5	8.9	9.2	9.6	9.2	9.4	9.2	10.1	10.6
NPL ratio (banking sector)	19.1	18.0	17.1	18.0	18.0	17.7	17.1	16.9	17.4
	% of GDP
General government revenues	33.8	35.7	35.5	..	..	..	..	..	..
General government expenditures	35.3	32.8	33.6	..	..	..	..	..	..
General government balance	–1.5	2.9	1.9	..	..	..	..	..	..
Primary balance	..	..	..	..	..	..	..	..	..
Gross public debt	12.6	12.0	12.3	..	..	..	..	..	..
	% of GDP
Debt of nonfinancial corporations (nonconsolidated)	..	..	..	..	..	..	..	..	..
Debt of households and NPISHs2 (nonconsolidated)	..	..	..	..	..	..	..	..	..
	% of GDP (based on EUR), period total
Goods balance	7.3	11.7	9.6	12.4	9.6	8.5	8.5	8.6	4.8
Services balance	–2.0	–1.8	–2.1	–1.6	–2.2	–2.6	–2.1	–1.8	–0.7
Primary income	–2.7	–2.5	–3.1	–1.3	–4.8	–3.1	–3.2	–0.6	–3.7
Secondary income	–0.6	–0.5	–0.6	–0.7	–0.2	–0.4	–1.0	–0.3	–0.5
Current account balance	2.1	6.9	3.8	8.9	2.4	2.4	2.2	5.8	–0.2
Capital account balance	0.0	–0.1	0.0	0.0	–0.1	0.0	–0.1	0.0	–0.1
Foreign direct investment (net)3	0.5	1.4	–0.5	–0.3	–0.3	–1.5	0.0	1.2	–0.5
	% of GDP (rolling four-quarter GDP, based on EUR), end of period
Gross external debt	31.2	28.2	29.2	29.5	29.7	29.8	29.2	27.5	30.1
Gross official reserves (excluding gold)	21.3	23.6	26.0	25.0	25.5	26.2	26.0	26.4	26.8
	Months of imports of goods and services
Gross official reserves (excluding gold)	12.3	13.7	15.0	14.4	14.8	15.2	15.0	15.2	15.6
	EUR million, period total
GDP at current prices	1,392,185	1,410,411	1,521,628	333,112	363,984	401,915	422,618	343,514	292,334
Source: Bloomberg, European Commission, Eurostat, national statistical offices, national central banks, wiiw, OeNB.
1 Foreign currency component at constant exchange rates.
2 Nonprofit institutions serving households.
3 + = net accumulation of assets larger than net accumulation of liabilities (net outflow of capital).
– = net accumulation of assets smaller than net accumulation of liabilities (net inflow of capital).

Outlook for selected CESEE countries

CESEE-6: deepest downturn after transformational recession, uncertain recovery; Russia: economy expected to recover gradually ^{9 , 10}

Table 1: OeNB-BOFIT GDP projections for 2020 to 2022 compared with the IMF forecast  

	Eurostat/Rosstat	OeNB-BOFIT projections October 2020			IMF WEO forecast October 2020
	2019	2020	2021	2022	2020	2021	2022
	Year-on-year growth in %
CESEE-6	3.9	–5.0	3.8	3.6	–4.8	4.6	4.2
Bulgaria	3.4	–5.3	4.3	3.4	–4.0	4.1	3.7
Croatia	3.0	–8.6	4.9	4.1	–9.0	6.0	4.4
Czech Republic	2.3	–5.3	2.3	3.7	–6.5	5.1	4.3
Hungary	4.9	–6.3	5.2	3.3	–6.1	3.9	4.0
Poland	4.2	–4.2	4.1	3.6	–3.6	4.6	4.5
Romania	4.1	–4.9	3.3	3.6	–4.8	4.6	3.9
Russia	1.3	–4.0	2.4	2.2	–4.1	2.8	2.3
Source: IMF World Economic Outlook (WEO) of October 2020, Eurostat, Rosstat, OeNB-BOFIT projections.

In Russia, GDP growth ¹² is expected to contract by 4% in 2020 but return to a moderate growth rate of 2.4% next year. The Russian economy has had to endure the combined effects of the COVID-19 pandemic and an upheaval in oil markets. The risk of a weaker-than-expected outcome is significant due to the continuing uncertainty related to COVID-19 and commodity market developments.

1 CESEE-6: unprecedented crisis with severe growth impact

In 2021, average economic growth in the CESEE-6 region will come to 3.8%, and for 2022, we expect some leveling off to 3.6%. Countries with the strongest slump in 2020 (namely Croatia and Hungary) will see the strongest recovery next year, with growth rates reaching around 5%. For the Czech Republic, however, we foresee a rather subdued recovery for country-specific reasons. For the CESEE-6 average, GDP losses are expected to be compensated only in the course of 2022.

Accommodative monetary policy to continue but challenges ahead

Tighter fiscal stance from 2021 onward

COVID-19 crisis weighs strongly on private consumption

Public consumption growth is expected to contribute positively to GDP growth in all CESEE-6 countries in 2020. However, despite support packages for households and corporates, public consumption growth will weaken, compared to previous years, in all countries with the exception of Croatia and the Czech Republic, both of which have introduced relatively sizable support packages. In 2021 and 2022, public consumption growth in the CESEE-6 countries will slow down further compared to 2020, possibly due to limited fiscal space. Only in Hungary will growth gain speed because of carry-over effects from 2020 and the upcoming ­parliamentary elections.

Gross fixed capital formation will be negative in 2020 in all CESEE-6 countries with the notable exception of Romania. The drop will be strongest in Poland (–7.6% in 2020, following a growth rate of above 7% in 2019). In Romania, gross fixed capital formation accelerated by 16% in 2019 and is expected to come to 3.5% in 2020 due to a good first half of the year. The lockdown in spring 2020 meant a temporary standstill for many projects in the CESEE-6. Furthermore, an uncertain future, financial constraints or shortage of labor from abroad due to travel restrictions (particularly in the construction sector) will reduce investment activity visibly in 2020. For 2021, we foresee a recovery, which will also be based on EU funds. The recovery will be muted, though, by tightening financing conditions, a rising number of bankruptcies and idle capacities.

Our export growth projections are in line with the MPE assumption on euro area imports. Accordingly, export growth will collapse in 2020 in all CESEE-6 countries, with growth figures ranging between –30.5% in Croatia (here, the ­service sector including tourism exports weighs on growth) and around –14% in Hungary and Romania. Importantly, due to weaker global demand, export growth had already lost some steam in a number of CESEE-6 countries prior to the COVID-19 crisis. Most CESEE-6 countries are strongly integrated in supply chains, especially of the automotive sector, which has been particularly strongly hit by the crisis. For 2021 and 2022, we expect a rather modest recovery in line with assumptions on euro area imports. Import growth in the CESEE-6 will turn ­negative in 2020 due to both weaker domestic demand and lower export growth, given the high import content of traded goods. In 2021, both imports and exports will recover. In sharp contrast to the global financial crisis ten years ago, the contribution of net exports in 2020 will be clearly negative in all CESEE-6 countries, particularly in Croatia and Hungary (reaching –3.2 and –3.3 percentage points, respectively). Only for Poland do we expect a positive contribution of net exports in the current year. From 2021 onward, we expect the contribution of net exports to become slightly more favorable in most CESEE-6 countries.

Risks to CESEE-6 projections point downward

Economic growth in the CESEE-6 countries depends largely on economic growth in their trading partners. Therefore, higher (lower) growth of the world economy or of the euro area, in particular, than assumed in our baseline scenario would translate into higher (lower) growth prospects for the CESEE-6. However, we see downside risks to external growth due to the negative impacts of an emerging second wave of COVID-19 infections in the CESEE-6 trading partners. In all euro area countries, COVID-19 infection rates have recently increased strongly, with some hotspots emerging, such as France and Spain. Infection rates are now on the rise also in Germany, one of the most important trading partners of the CESEE-6.

On the upside, the CESEE-6 countries would benefit particularly strongly, compared to other EU countries in relation to their GDP, from the July European Council agreement on the EU recovery instrument Next Generation EU (NGEU) for the period from 2021 to 2026 and the multiannual financial framework (MFF) for the period from 2021 to 2027 – even though it is currently not clear (1) whether the agreed package will remain the same after the adoption of the EU budget later this year, (2) when the concrete pay-outs can start in 2021 and (3) to which extent the available funds can be absorbed domestically. Better-than-assumed usage of the MFF could lift our projections. In any case, the likely overlap of projects in 2021 and 2022 stemming from the current and the future MFF period could stimulate investment more strongly than expected in some, but not all, countries.

However, different points of view in several political areas, such as migration or climate policy, open and deepen trenches between the EU and some CESEE-6 countries. Furthermore, some CESEE-6 countries’ deficiencies in aligning with the EU’s democratic standards are challenging these countries’ relations with other EU members and present a downside risk for the countries concerned if the EU were to condition the pay-out of EU funds on respecting the rule of law. This could also pose a more general downside risk to all CESEE-6 countries if potentially ­affected countries vetoed the NGEU.

Regarding Brexit, it is still unclear how the agreement between the EU and Great Britain will be designed after transitional regulations will expire in ­mid-2021. A hard Brexit cannot be ruled out and could likely impact our growth projections negatively, especially via trade disruptions.

In the context of international trade, disruptions in supply chains could last longer and leave deeper traces than assumed. On the other hand, a relocation of production to European countries in the process of shortening supply chains could also give a positive impetus to trade in the CESEE-6 region. Concerning the automotive sector, a slower-than-assumed recovery resulting from a combination of the COVID-19 crisis-related containment measures and climate-related policies would impact several CESEE-6 countries more strongly than expected.

On the national level, there are political risks, e.g. in Bulgaria, where strong opposition against political elites has been on the rise. More generally, demonstrations against potential new lockdown measures cannot be ruled out, either.

Second-round effects of the COVID-19 crisis are difficult to assess and present a downside risk to our forecast. In our view, additional risks to our baseline projections – namely risks arising from the phasing-out of loan moratoria, wage support, short-time work schemes, tax deferrals or other measures implemented to protect households and companies from the immediate consequences of the coronavirus-induced slump – seem contained overall. In our baseline, we assume a gradual and well-communicated phasing-out of these support measures as is suggested by recent extensions and a more stringent targeting of moratoria and support schemes in many countries. However, an unexpected or too early phasing-out could result in a stronger-than-­expected increase in nonperforming loans, lower credit activity or a stronger rise in unemployment. Furthermore, a high degree of uncertainty may prevail among economic agents, both for households and corporates, which might result in higher-­than-assumed precautionary saving or in lower-than-assumed investment activity.

We also see moderate downside risks to our growth projections coming from a potentially less accommodative monetary policy in light of modestly accelerating inflation rates in the CESEE-6 countries, in particular in the inflation-targeting countries. In the Czech Republic, for example, the inflation rate is already above the inflation target and thus somewhat limits the space for more accommodative monetary policy measures.

2 Projections for Bulgaria, Croatia, the Czech Republic, Hungary, ­Poland and Romania

Bulgaria: severe GDP contraction this year and increased political uncertainty

This baseline forecast is subject to several country-specific uncertainties. First, on the downside, the economic outcome of the summer season is, at the time of writing, still not fully visible. On the back of an intensified spread of the coronavirus in the middle of the summer of 2020, preliminary data indicate that the number of foreign tourists in the summer season amounted to only about 80% of the number recorded in 2019 and, as a result, hotels did either not open or had to shut ahead of schedule. Moreover, the recovery of several high-frequency indicators, especially of retail sales, was more restrained during the summer months than for the country’s regional peers. Second, it is currently not clear when the economic policy measures adopted to mitigate the impact of the recession will terminate. The main wage support scheme – the so-called 60:40 scheme – terminated already at the end of September 2020, but there are discussions on its prolongation, whereas a second scheme with a far smaller dotation targeting tourism, transportation companies and self-employed persons should last until end-2020. Loan repayment moratoria are scheduled to remain active until end-March 2021. Amid continuing mass anti-government protests, several government support measures might ­remain in place until the next parliamentary election, which will either be a snap poll or take place at the scheduled date in March 2021. Political instability could also continue after the elections as traditional parties have lost support and new populist movements are on the rise, potentially hampering coalition building and thus the timely response to the crisis-induced economic shortfall.

On the upside, we must consider that Bulgaria belongs to the EU countries that would benefit most from the NGEU (with an average share of 2.7% of its 2019 GDP expected annually during the period from 2021 to 2026, according to the July European Council agreement). This could stimulate more gross fixed capital formation than assumed in our forecast. Last but not least, Bulgaria’s participation in ERM II since July 2020 and in the EU banking union as of October 2020 as well as the country’s gradual process toward euro adoption in the next few years will help anchor macrofinancial stability.

Croatia: downward revision due to abrupt end of tourist summer season

We also revise the composition of growth drivers in Croatia. Private consumption is now expected to drop by less than envisaged in April, namely by 6.6% year on year. After a strong contraction related to lockdown measures in the second quarter of 2020, we are expecting a substantial rebound in the third quarter and subsequently a gradual further recovery of consumption, supported by government measures. In September 2020, the Croatian government announced, for instance, the prolongation of the wage support scheme until end-2020 (with tightened eligibility criteria) and planned income tax cuts effective from January 1, 2021. The prolonged uncertainty and slack in the labor market will likely lead to a lag in the recovery of durable goods consumption.

Gross fixed capital formation is expected to shrink by 10% year on year in 2020. Investments already contracted sharply in the first half of 2020 and we do not expect a noteworthy recovery in the second half of the year given high economic uncertainty. Loan repayment moratoria were still in place at the time of writing and used by many firms, likely masking the solvency issues of some firms. Bankruptcies and lingering uncertainty will likely subdue private investments in the coming years. However, EU funds play an important role for investments in Croatia and will ­support the recovery as Croatia is likely to be allocated substantial funds in the EU budget negotiations.

The realized contraction in exports and imports in the first half of 2020 has led us to revise downward our forecast for both components. Given the realized ­dynamics in the first half of 2020 and the fact that the tourist season was cut short in August, we now expect a strong negative contribution of net exports to GDP growth in 2020. We expect a rebound in tourism in 2021, but not to pre-crisis levels, due to several factors. In our baseline, a medical solution to the COVID-19 pandemic will not be widely available before mid-2021. Moreover, the severe ­economic downturn could dampen tourists’ ability and willingness to spend and leave scars on the supply side if tourism-related enterprises go out of business.

Overall, we continue to expect a moderate recovery of the Croatian economy, with growth rates of 4.9% and 4.1% year on year in 2021 and 2022. Croatia will therefore need some years to recover the GDP losses of the current crisis. The substantial allocation of EU funds is one of the few upside risks, amidst a highly uncertain outlook with many downside risks related to the evolution of the COVID-19 pandemic and macroeconomic imbalances. It also remains to be seen how the Croatian government will balance fiscal stimulus and fiscal consolidation needs in the light of its targeted adoption date for the euro.

Czech Republic: despite strongly accommodative economic policies, recovery from this year’s deep dive will be difficult

Economic growth in the Czech Republic had been gradually losing steam even before the COVID-19 shock hit in mid-March 2020, and the remainder of the year will continue to be heavily clouded by the COVID-19 pandemic. Nonetheless, we expect the latter to have a less detrimental effect than in the first six months to June 2020 as, inter alia, the profoundly dented but improving business sentiment indicators suggest. This is because most of the anti-coronavirus restrictions that are significant in economic terms have been wound down or largely relaxed. It currently seems that their re-introduction on a large scale would be met with a somewhat fiercer political, legal and social opposition than in spring 2020 despite rising numbers of COVID-19 infections. Moreover, the economic impact on ­private consumption and investment in the second half of 2020 will be mitigated by highly accommodative fiscal and monetary policy. Overall, we expect real GDP in the Czech Republic to plummet by 5.3% this year (while growth declined by 6.4% year on year in the first six months of 2020). The negative contributions of all expenditure-side GDP components will be counteracted only by accelerated growth in government consumption due to, inter alia, higher COVID-19-related expenditures (not only in healthcare).

Looking further ahead – even if the acute COVID-19 pandemic threat were to abate relatively soon (which does not seem very likely from the current perspective) – we expect economic recovery in the Czech Republic to remain rather moderate next year and to strengthen gradually toward the end of the forecast horizon. This is because private consumption, which is generally recovering, investment and export demand will be held back by several factors. On the one hand, the current fiscal and regulatory support measures for households and corporates will most likely terminate during the next months. As a result, a growing number of firms will be forced into bankruptcy, and unemployment will rise. On the other hand, several economic sectors are quite likely to suffer from long-lasting damage as a result of residual fear and prevalent uncertainty before demand and investment will return to their pre-pandemic behavioral patterns. In addition, the automobile industry, the heart of the Czech economy, was facing significant cyclical and structural demand- and supply-side challenges which will be compounded in the wake of the COVID-19 pandemic and ever-stricter EU-wide regulation. In sum, we expect domestic demand to be the main driver of relatively moderate but strengthening economic growth over the next two years. The contribution of net exports will be broadly neutral in 2021 and turn more significantly positive only toward the end of the forecast horizon.

The risks to our forecast are clearly tilted to the downside. In particular, the (structural) damage to the economy described above will be all the more ­pronounced the longer the COVID-19 pandemic and the ensuing restrictions and uncertainty will last.

Hungary: COVID-19 crisis causes bigger drop in GDP than expected

Following the lifting of the lockdown in May and June 2020, private consumption in Hungary will likely start to recover in the third quarter of 2020. Until end-2020, it will continue to benefit from a number of supporting policy measures taken in response to the COVID-19 pandemic. Also, the availability of various preferential loan facilities, together with central bank efforts to ensure smooth lending activity to households, should support consumption. Nevertheless, the contraction in employ­ment, the increase in the share of part-time workers and the slowing of real average wage growth (not least due to elevated inflation) will put a brake on the recovery.

Public consumption in Hungary decreased only modestly in the first half of 2020, and we expect it to expand during the second half of the year as a result of various fiscal measures taken in response to the COVID-19 pandemic. We expect public consumption to remain strong in 2021 as a whole, due to both the carry-over effects from late 2020 and increased spending in the second half of 2021 in line with the electoral cycle (parliamentary elections are due in spring 2022).

Gross fixed capital formation in Hungary was heavily hit by the COVID-19 crisis in the first half of 2020, and we expect a notable recovery of investment activity only from the second half of 2021. EU fund inflow under the 2021–2027 MFF should aid this recovery. On the other hand, capacity utilization in manufacturing fell sharply during the crisis, the outstanding stock of credit to the corporate sector declined sharply between March and July 2020 despite the beneficial effect of the debt service moratorium and the expansion of the Hungarian central bank’s various funding schemes, while corporate profitability was likely adversely affected by the COVID-19 crisis, reducing the availability of internal funds for investment as well.

External trade volumes contracted sharply during the second quarter of 2020.We expect trade volumes to start recovering in the second half of 2020, but given carry-over effects from the first half of 2020 and a strong base in the third quarter of 2019, both export and import volumes are expected to decline substantially in full-year 2020, resulting in a negative contribution of net real exports by almost 3 percentage points. Exports and imports should recover sharply in 2021, with net real exports again contributing positively to the overall GDP growth rate. With import growth overtaking export growth in 2022 in line with the further recovery of domestic demand, the growth contribution of net real exports is expected to become broadly neutral.

Poland: partial recovery in 2021 albeit still marked by COVID-19 effects

In 2021, the Polish economy is expected to grow by about 4.1%. While growth will be supported by a beneficial base effect, it will not be larger in absolute terms than the previous decline, as economic hysteresis effects and the number of ­bankruptcies postponed to 2021 will have dampening effects. Exports will start ­expanding again, driven by the recovery of demand in both the euro area and other parts of the world. However, foreign demand will recover substantially less strongly than it previously shrank. Moreover, some Polish export companies might go bankrupt while others will find it difficult to enter the export business in the ­current circumstances. Hence, export growth in 2021 is expected to come in at about 7%, only partially offsetting the previous decline. Domestic demand will show a similar pattern, with growth predicted to reach about 4.5%. Thus, both exports and domestic demand will render a large contribution to overall GDP growth in 2021.

As a result of the combined strong contraction of both export and domestic demand, imports will fall by about 11% in 2020, even more strongly than ­exports. Thus, there will be a positive contribution of net exports to GDP growth of more than half a percentage point. By contrast, in 2021, import growth is ­forecast to outpace export growth, as pent-up domestic demand will compound the effect of restarting foreign demand growth. This will imply a swing of the ­contribution of net exports to GDP growth into negative territory, to reach about –0.5 percentage points.

Both private consumption and gross fixed capital formation will register severe year-on-year contraction in the second half of 2020, albeit less severe than in the second quarter of 2020, especially in the case of private consumption. In the full year of 2020, private consumption is foreseen to contract by 6.5%, reflecting the comparatively low level and short duration of unemployment benefits and the high uncertainty among consumers, who likely spend only a fraction of the income ­support received in various forms (including partial exemptions of social security payments and banks’ moratoria) out of precautionary motives. Public consumption will rise strongly countercyclically but it has a limited weight in overall GDP growth. Gross fixed capital formation is forecast to contract by 7.6% in the wake of lacking demand. A deeper contraction will likely be avoided thanks to fiscal support for companies, a more optimistic outlook for 2021 and larger public ­investment, which should offset the impact of the fading-out EU funding cycle on local governments and (publicly owned) companies. In 2021, domestic demand components will grow again, although the route toward normalization is not likely to be straightforward. Private consumption will benefit from pent-up demand while being held back by adverse effects from bankruptcies and the deteriorated labor market situation. Public consumption growth will moderate, but not fully reverse. Gross fixed capital formation will benefit from restarting foreign and ­consumer demand and from continuously stronger public investment, underpinned by the overlapping of old and new MFF funding cycles.

Romania: recovery subject to fiscal policy uncertainty

Turning to individual demand components, retail sales suggest that the recovery in private consumption has proceeded well. Moratoria increased households’ room for maneuver while government-supported furlough schemes, in particular, averted a steep rise in unemployment. Income losses under furlough schemes and short-time work, precautionary savings as long as uncertainties remain elevated as well as gradually rising unemployment will restrict private consumption growth, however. Given the strained fiscal situation, hardly any support from fiscal policy can be expected in the coming years. In this respect, uncertainties are very high as a fiscal strategy will only be available after the parliamentary election scheduled for early December 2020. It is still unclear, moreover, whether and when the parliamentary decision to stick to a 40% pension expenditure hike, as opposed to the 14% hike envisaged by the minority government, will be enforced. If it will be enforced, this step will probably go hand in hand with counterbalancing budgetary measures.

After gross fixed capital formation (supported by vivid construction activity) showed positive year-on-year growth in the first half of 2020, the investment growth outlook for Romania appears encouraging. Gross fixed capital formation will benefit from EU funds allocated to Romania via the EU’s multiannual budget for the period from 2021 to 2027 and remaining funds flowing from the 2014 to 2020 multiannual budget. Plans for new motorways and for the modernization of railway lines (both partially EU funded) have already been announced. On top of this, a substantial upside risk stems from the EU’s economic recovery instrument NGEU. Moreover, state-guaranteed loans for corporates (under the IMM Invest Romania Program, which was introduced in response to the COVID-19 crisis) continue to positively affect investment activity. In the medium term, Romania could also benefit from a reallocation of production capacities as multinational ­European companies might try to increase capacities in Europe to make production chains less vulnerable to global disruptions.

The resumption of production of the two major car producers Dacia and Ford in May 2020 bodes well for a recovery in exports in quarter-on-quarter terms in the third quarter of 2020. With year-on-year growth in industrial production still clearly negative in July 2020, export recovery might turn out to be sluggish, however. The recovery in external demand, as predicted in our external assumptions, will result in positive export growth in 2021 (on top of the base effect) and 2022. The growth contribution of net exports will remain negative, however, as the projected pick-up in domestic demand will entail a marked rise in imports.

3 Russian economy expected to recover gradually

Private consumption has been a major factor behind Russia’s sharp GDP contraction. The lockdown and other restrictions implemented to deal with the spread of the coronavirus have cut consumption substantially. Consumption is also restricted by a strong decline in real disposable income and by increased unemployment. Since the lifting of most COVID-19 restrictions, a brisk recovery in private consumption appears to be underway. The recovery in consumption is expected to continue through the end of this year, but slowly and gradually.

Preliminary data show that fixed investment declined by 6% year on year in the first half of 2020. Uncertainty about the future makes firms reluctant to invest in new capital projects. Despite monetary policy easing, the sharp drop in corporate profits in the first half of this year has made the financing of investment more ­difficult for firms. Public-sector investment is constrained as some spending for investment is being redirected to social issues to relieve the economic impact of the COVID-19 pandemic on households.

The volume of Russian exports shrank in the first half of this year as the COVID-19 pandemic chewed through the global economy. In the second quarter of 2020, the volume of exports, however, already posted a slight growth even in annual terms. The improvement in goods exports has been supported by the brisk recovery of the Chinese economy. Russian exports should come back gradually and grow modestly next year as global commodity demand slowly revives. Russian ­imports are expected to fall substantially this year on the back of a contraction in domestic demand. In particular, the COVID-19 pandemic has caused a spectacular collapse in tourism abroad. In addition, the depreciation of the Russian ruble has dampened import developments. Imports should return to modest growth next year.

The three-year budget framework for the period from 2020 to 2022, which was approved by the Russian cabinet prior to the COVID-19 pandemic, anticipated increases in government spending. As the pandemic grinds on, budget spending is to be raised further this year to support the economy. With a substantial decline in budget income, government finances should finish 2020 deeply in the red. The government will cover some of the deficit with money set aside from oil earnings in the National Welfare Fund and by increasing domestic debt. From the start of next year, however, fiscal policy is planned to moderate again, reducing the supportive effect of public spending on the economy.

Oil market and COVID-19 infection rates mark crucial risks to our Russia forecast

Studies

What drives people’s expectations of euro adoption? – Evidence from the OeNB Euro Survey on selected CESEE countries

Peter Backé, Elisabeth Beckmann ¹⁴

Recently, the monetary integration of some countries in Central, Eastern and Southeastern Europe (CESEE) has gained new momentum. Based on data from the OeNB Euro Survey from 2007 to 2019, we present evidence on individuals’ expectations regarding accession to the euro area and examine how the framework that governs euro area accession, the different monetary policy regimes and de facto euroization affect expectations. We find that expectations have become less optimistic over time and that individuals’ uncertainty in forming expectations has increased. Exposure to de facto euroization increases optimism in expectations regarding euro introduction and decreases uncertainty. Individuals who trust their national central bank and the EU expect accession to the euro area to take place sooner. Expectations of inflation or depreciation of the local currency are related to more pessimistic expectations regarding euro introduction. Monetary expectations (i.e. inflation and exchange rate expectations) play a stronger role for EU member states than for EU candidates and potential candidates; regarding trust in institutions the picture is reversed.

JEL classification: D12, D84, E50, O52

Keywords: euro area accession, expectations, uncertainty, CESEE

Against this background, this paper focuses on two issues: What expectations do people in the CESEE region have regarding euro adoption? And what is driving these expectations? This is a highly relevant research topic given that euro adoption expectations do shape important economic and financial decisions among individuals, for example in the realm of saving and borrowing decisions when it comes to the choice of the currency in which assets and liabilities are denominated.

More specifically, we concentrate on exploring euro adoption expectations in ten CESEE countries that are not (yet) members of the single currency area, namely six EU members – Bulgaria, Croatia, the Czech Republic, Hungary, Poland and Romania – as well as four EU candidates and potential candidates (CPCs) from the Western Balkans – Albania, Bosnia and Herzegovina, North Macedonia and Serbia. Our analysis is based on data from the OeNB Euro Survey, which is, to our knowledge, the only dataset covering this issue for CESEE EU members and for CPCs. ¹⁵ We cover developments from 2007 to 2019. ¹⁶ We first describe the distribution of expectations and how uncertain individuals are when forming expectations of euro adoption. We then focus on how (de facto) euroization as well as differences in monetary policy regimes and institutions affect expectations. Of course, there are many more aspects of how individuals form their expectations regarding euro adoptions that could be analyzed. However, we prioritize depth over breadth and have limited the scope of our analysis to those aspects that are related to institutional determinants. We do not address heterogeneities that are related to individuals’ cognitive abilities, preferences or beliefs.

Gaining a better understanding about the determinants of euro adoption ­expectations is crucial from a policy perspective, given that these expectations ­impact on numerous economic and financial decisions people take. Moreover, ­implementing strategies for preparing euro adoption is certainly facilitated if ­expectations are well aligned with policy plans.

Our analysis is related to the growing effort by central banks around the world to gain a more precise understanding of how households form expectations and how these expectations affect their behavior. ¹⁷ This effort is reflected in the strong increase in research on households’ expectations: Between 2000 and 2005, on ­average, 41 publications referenced on EconLit per year refer to “expectations” in the abstract and mention “households” in the main body of the paper. In the years from 2015 to 2020, this admittedly very rough indicator increases to 125 publications on average per year. And for the first half of 2020 alone, there are already 140 publications with these characteristics. We will not attempt to review or do justice to this mushrooming literature in this paper. We note, however, that we are not aware of any other analytical paper that has studied the determinants of euro adoption expectations in CESEE. Based on OeNB Euro Survey data, Scheiber (2019a and 2019b) addresses the question of whether euro adoption expectations have an impact on people’s propensity to hold euro cash. He finds a positive and significant influence of expected euro adoption on the likelihood that individuals hold euro cash, however not on the amounts of euro cash held.

Our study is structured as follows: In section 1, we describe the data we used, and section 2 presents results on how households’ expectations regarding euro ­introduction are distributed and how certain households are in forming expectations. Section 3 presents our empirical approach. In section 4, we discuss which factors determine euro introduction expectations, before summarizing our findings and concluding.

1 Data: the OeNB Euro Survey

Each sample reflects a country’s population characteristics in terms of age, gender, region and ethnicity. Weights are calibrated separately for each wave on census population statistics.

The survey questionnaire elicits a rich set of information on socioeconomic characteristics, indicators of wealth and finances, individual beliefs, expectations and trust. The questionnaire is composed of a core set of questions regarding the extent of euroization as well as varying questions that focus on a specific research question. One of the central aims of these specific research questions is to understand the determinants of euroization in the CESEE-10 countries. The volatility of inflation and the exchange rate and individuals’ inflation and exchange rate expectations as well as expectations regarding accession to the euro area are important determinants of the different dimensions of euroization (e.g. Ize and Levy Yeyati, 2003; Jeanne, 2005; Stix, 2013; Fidrmuc et al., 2013; and Brown and Stix, 2015).

The central variable for our analysis, which measures expectations regarding accession to the euro area, is based on the following question:

This question was included in the survey waves of 2007, 2008, 2010, 2011, 2014, 2017, 2018 and 2019 with a total of around 92,000 observations. ¹⁸ Due to a different research focus, the question on euro introduction expectations was not asked in the survey waves of 2012, 2013, 2015 and 2016. As we believe recent ­developments are of more interest and want to avoid cluttering the descriptive analysis below, we pool the waves 2007−2008 and 2010−2011. Despite the fact that the time series of euro introduction expectations is not without interruption, the long time span covered by the survey is a unique asset for our analysis: The survey covers a time span of 13 years, albeit not at an annual frequency, with no changes to question wording or survey methodology, which is a rare asset. ¹⁹ Moreover, the OeNB Euro Survey has been conducted in a way that provides comparable data for ten countries with diverse institutional and policy backgrounds. Finally, the questionnaire also includes questions on inflation and exchange rate expectations as well as on trust in institutions, which makes it possible to analyze how different expectations and trust relate to each other. Nevertheless, it is important to bear in mind the survey was not designed as an expectations survey, where it has become the established practice to ask questions about expectations in (1) qualitative form, i.e. asking about the direction of changes, (2) quantitative form, i.e. asking for a point estimate of expected changes in percent, and (3) probabilistic form, i.e. asking respondents to evaluate the likelihood of economic variables being within specific ranges (for example, Manski, 2004; Van der Klaauw et al., 2008; Deutsche Bundes­bank, 2019; European Central Bank, 2020b).

Moreover, expectations about euro introduction are likely influenced not only by policymakers and institutions but also by individuals’ preferences and wishes. In the current analysis, we do not attempt to disentangle these two aspects – also due to a lack of additional data on individuals’ wishes. ²⁰

2 Euro introduction expectations: past and present

When we look at the evidence to come up with answers to these questions, we must bear in mind that the CESEE-10 countries we analyze are very diverse with respect to their current monetary policy regimes and with respect to euro area accession policies. In the following, we will first give a quick overview of the framework that governs euro area accession, and then present results on how ­expectations are distributed across countries and over time. We will then focus on three aspects of this distribution: the role of monetary policy regimes for expectation formation, the role of the euro area accession framework and the role of uncertainty.

2.1 Distribution of euro introduction expectations from 2007 to 2019

Three issues need to be noted in this context: First, expectations that are in line with the technical rules may also turn out to be too bullish, given that euro area accession requires a high degree of sustainable convergence, which may not yet be fully in place at the earliest technically feasible point in time; and in fact, euro area accession in the minimum timeframe so far has been the exception rather than the rule. Second, joining the euro area in the third year after EU accession presupposes that a country is willing and sufficiently prepared to enter ERM II shortly after EU accession. Again, this may not necessarily be the case; in fact, in the past it was only the case for two out of the five CESEE euro area countries. Third, we take the OeNB Euro Survey question on euro introduction expectations to refer to euro area accession and not to a unilateral adoption of the euro. We think this is a reasonable specification given that no CESEE country has been considering a go-alone strategy toward adopting the euro during the sample period and that EU institutions have repeatedly stressed elementary objections against a potential unilateral euro adoption.

We now turn to the question of how expectations are distributed across countries and over time. Chart 1 shows the developments in EU member states from 2007 to 2019. Strikingly, expectations have become less optimistic ²⁴ over time in the majority of countries, as expected euro adoption lead times have become longer with the passage of time. “Never” answers have also tended to rise over time – especially in the Czech Republic, Hungary and Poland. We see an exception in Croatia, where expectations oscillated quite a bit over time but were somewhat more optimistic in 2019 than they had been back in 2007. ²⁵ In turn, the development of “don’t know” shares has been diverse across countries. It is particularly interesting to note that it has substantially fallen in recent years in Croatia, while increasing to very high levels in Bulgaria and Poland. The recent decrease of “don’t know” ­responses in Croatia is likely also related to the very active information campaign by the authorities, in particular the central bank.

A multitude of partly related factors come to mind as possible explanations for the lengthening of expected lead times. We can only sketch a number of them briefly, while emphasizing that their relevance differs from country to country. Upon EU accession, euro adoption strategies of CESEE authorities were rather ambitious in most cases; only the Czech Republic (and to some extent Romania) took a more gradual approach. ²⁶ In a number of countries, the ambitious plans proved unfeasible for a variety of reasons. As a consequence, timelines were lengthened, and later dropped in a number of cases. The sovereign debt crisis in several euro area countries certainly affected perceptions about cost-benefit balances of euro area membership. At the same time, inflation targeting and flexible exchange rates were seen to serve some countries well, while fixed and quasi-fixed pegs also proved durable. These factors certainly impacted on people’s euro adoption expectations in the six CESEE EU member states covered here. Changes in expectations, in turn, equally surely fed back into policy positions regarding euro adoption.

As Bulgaria and Croatia joined ERM II in July 2020, it is interesting to take a closer look at the development of euro adoption expectations in these two countries in the recent past. ²⁷ To do so, we briefly recall at what stage the preparations for closer monetary integration were when the field phases of the last three OeNB Euro Survey waves took place (i.e. in the fall of 2017, 2018 and 2019). As of the fall 2017 wave, the Bulgarian authorities had indicated their intention to apply for ERM II entry (once ERM II stakeholders were ready to accept such an application). In Croatia, the central bank issued, in the fall of 2017, a strategy document on euro adoption which arrived at the conclusion that it would be favorable for the country to proceed toward joining the euro area (without indicating a timeline). In July 2018, ERM II stakeholders clarified, against the backdrop of EMU deepening (and, in particular, the creation of banking union), that countries willing to join ERM II also ought to enter into close cooperation with the ECB in the area of banking union. At the same time, Bulgaria expressed its firm intention to join ERM II within a year. In Croatia, the government adopted a euro introduction strategy in May 2018, based on an earlier central bank strategy document. Moreover, the central bank communicated the strategy very actively in numerous road shows across the country. As of fall 2019, preparations for ERM II entry and, alongside, for close cooperation with the ECB, were advancing for Bulgaria and Croatia, while it was not yet clear how much time they would take until being completed. How did ­expectations develop during this period? In Bulgaria, “don’t know” dominated in recent waves, with a slight decline from 2017 to 2018, followed by almost no change in 2019 (57%). Notably, only about one-third of respondents had expectations of euro adoption that relate to a specific introduction year in 2018 and 2019 (slightly up from 28% back in 2017). Zooming in on the latter, we see a shift to more optimistic expectations from 2017 to 2018, which was partly reversed in 2019 (as overly optimistic expectations of a rapid euro adoption decreased). “Never” ­responses hover around 10%, with little change. In Croatia, we see that expectations have become more optimistic in recent waves (including also a rise in expectations of a very fast euro adoption), while the share of “never” responses ­decreased mildly from already low levels. At the same time, the share of respondents who answered that they “don’t know” fell substantially from 2014 to 2017 and again from 2018 to 2019.

Chart 2 depicts how expectations of euro introduction have changed over time in the CPCs. For this country grouping, heterogeneities are particularly pronounced. Bosnia and Herzegovina is a rather extreme case, with very high shares of “don’t know” answers. Among the remainder of respondents, “never” answers exceed the combined shares of those respondents that expect euro adoption at any future point in time. The share of the latter is also rather low in Serbia and roughly equals the “never” shares that have hovered around 30% during the past decade (in 2018 even getting close to 40%). In contrast, “don’t know” shares have substantially fallen in Serbia in recent waves. A considerable and in fact rising “never” share is also characteristic for North Macedonia, while the opposite can be observed for Albania where this answer category was starkly lower than in the other three CPCs in the last three waves. Moreover, in recent years, Albania also boasts the by far smallest “don’t know” shares among the four CPCs covered here. Comparing expectations in 2007 and in 2019, Albania stands out as the only CPC where expectations have become more optimistic. The opposite is true for Serbia and North Macedonia. Expectations in Bosnia and Herzegovina have barely altered. It needs to be noted that expected EU accession timelines for the CPCs have also slipped, as time went on, which in turn has also shifted expectations toward a later euro adoption.

How do the differences in monetary policy regimes across the CESEE-10 countries relate to euro adoption expectations? To address this question, we group countries based on their monetary policy regimes and compare euro adoption ­expectations across these groupings, i.e. we capture in how many years (mean and median) respondents expect the euro to be introduced in their respective home countries. Table 1 shows that there were surprisingly contained differences in ­expectations by different country groups in 2019. (Of course, these fairly moderate differences could either point to a limited impact of regimes on expectations or to other factors that dampen these differences.) An interesting distinction can be seen between EU member states and CPCs, as regards fixed versus floating regimes: While there is a clear difference between these two types of regimes in EU members in terms of expectations, this is not the case in CPCs. Moreover, we also examined correlations between exchange rate volatility and euro adoption expectations (mean, median and individual expected euro adoption). Here, we find that exchange rate volatility in the 12 months before a survey wave is mostly negatively correlated to the expected lead time until euro introduction. ²⁸

Table 1: Expectations across countries and monetary policy regimes  

	Mean	Median
	Years until expected euro introduction
EU member states	7.5	6
EU candidates and potential candidates	10.5	8
Fixed exchange rate (de jure or de facto): BG, HR; MK, BA	7.4	6
Float or managed float: CZ, HU, PL, RO; AL, RS	9.7	6
EU member states: fixed	5.4	4
EU member states: float	9.1	6
CPCs: fixed	10.9	10
CPCs: float	10.3	7
Inflation targeting	9.7	6
No inflation targeting	7.4	6
Source: OeNB Euro Survey (2019).
Note: The sample is reduced to respondents who name a year in which they expect the euro to be introduced, i.e. “don’t know” and “never” responses are dropped.

How is the framework for euro area accession reflected in expectations? We focus on the issue of overly optimistic expectations and display their development over time. Chart 3 shows the share of respondents with overly optimistic expectations, i.e. those who indicate a specific year in which they expect the euro to be adopted in their country that is not in line with the framework for euro introduction. Despite considerable variation over time, the share of overly optimistic expectations was lower, for most countries, at the end of the sample period than at the beginning. Among EU member states, overly optimistic expectations are clearly less widespread in countries in which authorities are reluctant or not eager at all to join the euro area in the foreseeable future, while the opposite is true for countries where authorities strive for progress toward euro adoption. The efforts of Croatia and Bulgaria (in the latter case, the renewed efforts) to advance on the road to the euro may have affected uncertainty but have not had any major effects on the share of overly optimistic expectations (some downward movement in Bulgaria, more mixed developments in Croatia). However, such policy efforts likely occasion a better understanding of the institutional framework in the general public and thus, if anything, moderate overly optimistic expectations. In CPCs, the share of overly optimistic expectations is higher than in CESEE EU member states. Presumably, this is mainly due to overly optimistic expectations about EU accession that add to other factors that can be considered to play a role for all ten countries under review here – in particular limitations in knowledge about euro area accession rules, but also uncertainty.

2.2 Euro adoption expectations and uncertainty

Research on expectations, in particular inflation expectations, has recently ­focused on understanding the role of uncertainty. For example, Ben-David et al. (2018) show that households differ in how uncertain they are in their expectations regarding personal and macroeconomic outcomes, which in turn affects their economic decisions. From a survey perspective, there are different ways to measure uncertainty. Brown and Stix (2015) and Dovern (2020) ask respondents directly to assess their uncertainty in expressing their expectations. An alternative has been to employ probabilistic questions, where respondents are asked to assess the likelihood of ­inflation or other macroeconomic outcomes falling within specified intervals. These responses are then used to calculate the standard deviation of the expected mean outcome for each individual. The standard deviation is interpreted as a measure of uncertainty, an approach which has, however, also been criticized (see e.g. Krüger and Pavlova, 2020). Finally, some researchers have argued that rounding is an expression of uncertainty (see e.g. Binder, 2017, and Manski and Molinari, 2010): Respondents report one – rounded – value rather than reporting a range. Rounding is certainly also an issue in our context, given that the OeNB Euro Survey asks respondents to indicate specific years rather than intervals or timespans (e.g. “during the first half of the 2020s”), which would seem to correspond more closely to individual expectations in a setting that is characterized by uncertainty.

Turning now to our dataset on euro adoption expectations, a first clear indication of uncertainty is the high share of “don’t know” responses, as documented in charts 1 and 2.

Chart 4 corroborates, based on the development of the standard deviation of the timespan until expected euro introduction, that uncertainty in euro introduction expectations has tended to increase over time. ²⁹

With regard to the issue of rounding, chart 5 confirms that our data contain substantial shares of answers that refer to years that are multiples of 10 in the six CESEE EU member states. ³⁰ For the three survey waves shown in the chart (but also more generally), the share of answers that are multiples of 10 ranges from 27% to 55%, while if evenly distributed it would be 10%. In chart 5, we juxtapose this share with the share of expectations that the euro will be adopted in 2020 from the vantage point of three different survey waves. By doing so, we illustrate the connection between rounding (i.e. uncertainty) and overly optimistic expectations. This link can be seen neatly when looking at the 2017 survey wave. At the time of that wave, the technically earliest possible year for euro adoption was 2021. We suppose that rounding pushed expectations for 2020 upward (i.e. that some respondents named 2020 as a rounded figure, while they may have actually been thinking of a range extending into the first part of the 2020s). One year later, in the 2018 wave, a number of respondents still expect that the euro will be introduced in their country in 2020, apparently thinking of the next year that represents a “round” figure, even though 2020 was already very near at the time of the 2018 wave. Rounding to multiples of 10 would also suggest that ­“underlying” expectations relate to fairly long intervals that are in themselves an additional indication for uncertainty.

3 Empirical framework and strategy

The large share of “don’t know” answers to the central question of our analysis also poses a challenge for our empirical analysis. One option would be to follow the usual practice and set “don’t know” responses to missing, thereby assuming these responses are in fact randomly distributed. However, considering the content of the question, this assumption would not be justified as it would ignore the extent of uncertainty surrounding euro introduction expectations. We therefore opt to include the responses in our analysis as a meaningful separate response option. In addition, the response behavior for the remaining responses shows that respondents tend to round their answers. Therefore, instead of following the prevalent practice of taking numerical responses at face value, we draw on Manski and Molinari (2010) and construct interval data from the survey responses. Based on both of these decisions combined, our dependent variable E for respondent i takes the values:

The outcomes are defined as mutually exclusive, i.e. a respondent cannot ­simultaneously be in categories 0 and 1. If the response of “within 10 years” is overly optimistic, the response will be coded as 0. The resulting dependent variable Ei is a variable where not all response categories can be ordered meaningfully, in particular outcomes 0, 4 and 5. Put differently, the distribution of the dependent variable is multinoulli. In our baseline specification, the probability of answering 0 to 5 is modeled as the multinomial logistic function G of respondents’ characteristics, monetary institutions and euroization:

where Si is a vector of respondent-specific controls, in particular sociodemographic characteristics and Mi is a vector of respondents’ economic expectations and trust in monetary institutions and Xi controls for respondents’ exposure to euroization and euro usage. We define category 3 (“expect euro introduction >20 years”) as the reference category, i.e. the probability of answering 0, 1, 2, 4 or 5 is compared to the probability of answering 3.

An alternative to estimating a multinomial logistic model would be to run separate regressions for the determinants (1) of “don’t know” and “never” responses and (2) of responses in years regarding expectations. For the first case, we would run logistic regressions, however, imposing a Bernoulli distribution on the dependent variable. For the second case, we would analyze the subsample of respondents that name a year of expected introduction only, likely introducing selection bias into the analysis. Considering these disadvantages, the main results are based on multinomial logit models; in robustness checks we also run separate logit and ­ordered logit models.

The control variables Si are informed by empirical results from the expectations literature and consist of gender, age, education and income (see e.g. Bryan and Ventaku, 2001a and 2001b; Easaw et al., 2013). ³¹ In analyzing the role of monetary institutions for expectations, we follow Mellina and Schmidt (2018) and Christelis et al. (2020) and control for trust in the central bank. ³² In addition, we control for trust in the stability of the local currency and in the stability of the euro. In an alter­native specification, we analyze how expectations regarding inflation and the exchange rate are correlated with Ei.

A recent body of research argues that humans cannot absorb all information and choose which information to attend to. Usually, people devote more attention to issues with which they are confronted more directly or more frequently and, as a consequence, they form clearer – though not necessarily more realistic – expectations on related matters. Against this background, we also control for respondents’ exposure to the euro. In particular, we include proxies for the extent of euroization in respondents’ immediate environment. We also analyze whether expectations are correlated with respondents’ financial choices, namely whether the ­respondent has a deposit or loan denominated in foreign currency. We further analyze whether respondents’ exposure to the euro affects formation of expectations by analyzing the role of foreign currency income and remittances and controlling for proximity to the euro area.

As not all control variables are available in all waves, we reduce the sample to those waves where we have a consistent set of controls, namely: 2014, 2017, 2018 and 2019. All specifications include country and wave fixed effects. Standard ­errors are clustered at the country-wave level. We estimate multinomial logit models. To ­facilitate interpretation of our results, we calculate average marginal effects and analyze some of the effects in more detail by calculating marginal effects at representative values. The categories of the dependent variable are defined by economic rationale; we check this definition and whether dependent categories could be combined by conducting Wald tests for combining dependent categories.

4 Determinants of euro introduction expectations

How does exposure to aspects of euroization affect people’s euro adoption ­expectations? That exposure indeed does have an impact is shown in table 2 (based on two alternative models ³³ ): Those who consider that holding euro cash is common and those that have foreign currency deposits are more likely to expect an early (overly optimistic) or relatively early (within a decade) euro introduction compared to those that do not. At the same time individuals displaying these euroization-related characteristics are less likely to give “don’t know” answers (i.e. they are in a better position to form expectations). The latter is also true for individuals who receive remittances. Those who have a regular income in euro are also more likely to expect a relatively early euro adoption and less likely to answer “don’t know” (the latter is only weakly statistically significant). The only euroization-­related characteristic that reduces the likelihood of “never” answers is the perception that it is common to have foreign currency deposits. Of course, we do not interpret these results as causal effects as some of the control variables may well be endogenous, i.e. respondents may choose to hold foreign currency deposits or loans because they expect accession to the euro area in the near future.

Table 2: How significant is exposure to euroization and the euro area for expectations?  

	Respondents expect euro introduction…
Dependent variable outcome category	Before theoretically possible	Within 10 years	Within 20 years	In more than 20 years	Never	Don’t know
Model 1
common to hold euro cash	0.022***	0.019***	–0.003	–0.006*	–0.005	–0.027***
	(0.008)	(0.007)	(0.005)	(0.003)	(0.008)	(0.008)
common to have foreign currency deposits	0.021**	0.001	0.008*	0.001	–0.035***	0.004
	(0.009)	(0.006)	(0.005)	(0.003)	(0.011)	(0.009)
has foreign currency deposits	0.036**	0.035***	0.012	0.000	–0.029**	–0.055***
	(0.018)	(0.007)	(0.014)	(0.006)	(0.014)	(0.012)
has local currency deposits	0.01	0.022***	0.017***	0.000	–0.026***	–0.024*
	(0.013)	(0.006)	(0.006)	(0.007)	(0.009)	(0.013)
has local currency loan	0.005	0.011*	–0.003	–0.001	–0.012	–0.001
	(0.008)	(0.007)	(0.005)	(0.003)	(0.009)	(0.009)
has foreign currency loan	–0.004	–0.009	0.011	0.007	0.009	–0.013
	(0.010)	(0.007)	(0.007)	(0.005)	(0.011)	(0.011)
N	32,575	32,575	32,575	32,575	32,575	32,575
Log-L	–45,810	–45,810	–45,810	–45,810	–45,810	–45,810
country and wave fixed effects	Yes	Yes	Yes	Yes	Yes	Yes
further control variables	Yes	Yes	Yes	Yes	Yes	Yes
Model 2
receives remittances	–0.003	0.011*	0.009*	0.008**	–0.002	–0.024**
	(0.013)	(0.006)	(0.005)	(0.004)	(0.014)	(0.010)
regular income in euro	0.016	0.022**	0.006	–0.005	–0.007	–0.032*
	(0.012)	(0.009)	(0.007)	(0.005)	(0.013)	(0.017)
N	39,880	39,880	39,880	39,880	39,880	39,880
Log-L	–54,862	–54,862	–54,862	–54,862	–54,862	–54,862
country and wave fixed effects	Yes	Yes	Yes	Yes	Yes	Yes
further control variables	Yes	Yes	Yes	Yes	Yes	Yes
Model 3
common to hold euro cash	0.022***	0.019***	–0.003	–0.006*	–0.005	–0.028***
	(0.008)	(0.007)	(0.005)	(0.003)	(0.008)	(0.008)
common to have foreign currency deposits	0.022**	0.001	0.008*	0.000	–0.035***	0.004
	(0.009)	(0.006)	(0.005)	(0.003)	(0.011)	(0.009)
has foreign currency deposits	0.038**	0.032***	0.011	0.000	–0.028*	–0.053***
	(0.018)	(0.007)	(0.014)	(0.005)	(0.014)	(0.012)
has local currency deposits	0.011	0.022***	0.016***	–0.001	–0.026***	–0.023*
	(0.013)	(0.006)	(0.006)	(0.006)	(0.009)	(0.013)
has local currency loan	0.005	0.011*	–0.003	–0.001	–0.012	–0.001
	(0.008)	(0.007)	(0.005)	(0.003)	(0.009)	(0.009)
has foreign currency loan	–0.004	–0.009	0.011	0.007	0.009	–0.013
	(0.010)	(0.007)	(0.007)	(0.005)	(0.011)	(0.011)
receives remittances	–0.01	0.009	0.007	0.009**	0.001	–0.016*
	(0.014)	(0.006)	(0.006)	(0.004)	(0.016)	(0.009)
regular income in euro	0.004	0.016	0.004	–0.005	–0.006	–0.013
	(0.014)	(0.011)	(0.008)	(0.006)	(0.014)	(0.020)
N	32,571	32,571	32,571	32,571	32,571	32,571
Log-L	–45,781	–45,781	–45,781	–45,781	–45,781	–45,781
country and wave fixed effects	Yes	Yes	Yes	Yes	Yes	Yes
sociodemographic control variables	Yes	Yes	Yes	Yes	Yes	Yes
Source: OeNB Euro Survey (2014−2019). Authors’ calculations.
Note: Multinomial logit results, average marginal effects reported. Further sociodemographic controls are included but not reported. Standard errors, in parentheses, are clustered at the country-wave level. The Wald test for combining dependent categories is significant for all outcomes of the dependent variable at the 1% level.

The significance and direction of effects remains the same if we re-estimate table 2 using alternative reference categories. For all combinations of outcome ­categories, having a foreign currency loan has no statistically significant effect on expectations. Both model 1 and 2 also control for how far from the euro area the respondents live. We find that distance has an extremely heterogeneous effect across countries, very likely related to cross-border commuting in some countries and urbanicity in others. ³⁴

Looking at EU member states and CPCs separately yields further insights. ³⁵ We do so by (1) including a dummy variable for CPCs in the model and (2) by splitting the sample into EU member states and CPCs. As regards significance, the main differences between the two country groupings relate to three respondent characteristics: (1) perception that it is common to hold euro cash: while individuals in CESEE EU member states who have this perception are more likely to expect relatively early euro adoption, this is not the case for people in CPCs; (2) those who state that they have no deposits are more likely to expect late euro adoption if they are CESEE EU citizens; this is not so for respondents in CPCs; and (3) receives ­remittances: individuals in CESEE EU member states to whom this characteristic applies are more likely to expect early or relatively early euro adoption; this is not the case for people in CPCs. Moreover, there are notable differences in the size of some significant effects. For example, having foreign currency deposits correlates with expectations much more strongly in CESEE EU member states than in CPCs.

Moving on to the second subset of determinants that we are interested in in this paper: Which role does trust in institutions and monetary expectations play in shaping euro adoption expectations? Our results are displayed in table 3, with model 1 focusing on trust and model 2 on monetary expectations.

Table 3 shows that those who trust in the euro, in the EU and in their national central bank are more likely to expect an early or relatively early euro adoption, while at the same time they are less likely to think that their country will never join the euro area. Trust in the local currency increases the likelihood of medium- to longer-term euro adoption expectations but has no impact on the likelihood of “never” answers. Those who expect inflation or depreciation of the local currency tend to be more likely to have somewhat more negative euro adoption expectations than those who do not.

Table 3: How significant are monetary expectations and trust in institutions for expectations?  

	Respondents expect euro introduction…
Dependent variable outcome category	Before theoretically possible	Within 10 years	Within 20 years	In more than 20 years	Never	Don’t know
Model 1
LC future stable	–0.002	0.017**	0.012**	–0.002	–0.013	–0.011
	(0.008)	(0.007)	(0.005)	(0.003)	(0.011)	(0.007)
EUR future stable	0.025***	0.026***	–0.006	–0.003	–0.049***	0.007
	(0.009)	(0.007)	(0.005)	(0.004)	(0.010)	(0.009)
trust in central bank	0.033***	0.024***	–0.001	–0.010***	–0.039***	–0.007
	(0.010)	(0.008)	(0.006)	(0.003)	(0.009)	(0.010)
trust in EU	0.049***	0.027***	0.001	–0.004	–0.074***	0.000
	(0.010)	(0.006)	(0.005)	(0.004)	(0.008)	(0.008)
N	31,875	31,875	31,875	31,875	31,875	31,875
Log-L	–44,534	–44,534	–44,534	–44,534	–44,534	–44,534
country and wave fixed effects	Yes	Yes	Yes	Yes	Yes	Yes
further control variables	Yes	Yes	Yes	Yes	Yes	Yes
Model 2
expect depreciation	0.011	–0.017***	–0.009*	0.002	0.027***	–0.014*
	(0.009)	(0.006)	(0.005)	(0.002)	(0.009)	(0.008)
expect inflation	–0.023**	–0.009*	0.008	0.008***	0.020**	–0.003
	(0.011)	(0.005)	(0.005)	(0.003)	(0.009)	(0.008)
N	33,636	33,636	33,636	33,636	33,636	33,636
Log-L	–47,418	–47,418	–47,418	–47,418	–47,418	–47,418
country and wave fixed effects	Yes	Yes	Yes	Yes	Yes	Yes
further control variables	Yes	Yes	Yes	Yes	Yes	Yes
Model 3
LC future stable	0.001	0.018***	0.013**	–0.001	–0.01	–0.020***
	(0.008)	(0.007)	(0.005)	(0.003)	(0.010)	(0.007)
EUR future stable	0.029***	0.022***	–0.007	–0.004	–0.050***	0.01
	(0.009)	(0.007)	(0.005)	(0.004)	(0.010)	(0.009)
trust in central bank	0.037***	0.024***	–0.001	–0.010***	–0.040***	–0.01
	(0.010)	(0.008)	(0.006)	(0.003)	(0.009)	(0.010)
trust in EU	0.049***	0.028***	0.001	–0.004	–0.076***	0.001
	(0.010)	(0.006)	(0.005)	(0.004)	(0.009)	(0.008)
expect depreciation	0.022**	–0.005	–0.006	–0.001	0.009	–0.018**
	(0.008)	(0.006)	(0.005)	(0.003)	(0.009)	(0.009)
expect inflation	–0.022*	–0.006	0.009*	0.009***	0.018*	–0.006
	(0.013)	(0.005)	(0.005)	(0.003)	(0.010)	(0.008)
N	29,010	29,010	29,010	29,010	29,010	29,010
Log-L	–40,786	–40,786	–40,786	–40,786	–40,786	–40,786
country and wave fixed effects	Yes	Yes	Yes	Yes	Yes	Yes
sociodemographic control variables	Yes	Yes	Yes	Yes	Yes	Yes
Source: OeNB Euro Survey (2014−2019). Authors’ calculations.
Note: Multinomial logit results, average marginal effects reported. Further sociodemographic controls are included but not reported. Standard errors, in parentheses, are clustered at the country-wave level. The Wald test for combining dependent categories is significant for all outcomes of the dependent variable at the 1% level.

Again, we look at the subsamples of CESEE EU members states and CPCs to examine possible heterogeneities among these two sets of economies. ³⁶ Two main points stand out: Regarding the size of the effects, trust in institutions has a larger impact in CPCs than it has in CESEE EU member states. As for significance, ­depreciation expectations have somewhat varying effects in CESEE EU members states as compared to CPCs, while expectations of inflation imply a higher likelihood that respondents expect a later euro adoption in CPCs than this is the case in CESEE EU member states.

We conduct several robustness checks. First, we rerun regressions including all control variables in models 1 and 2 of tables 2 and 3 jointly to examine issues of multicollinearity among other issues. Results do not change significantly and are shown in the annex (tables A3 and A4). Second, taking into account that our sample includes a very diverse set of countries we rerun regressions dropping one country at a time to ensure results are not driven by a single country. We do not find evidence that this is the case. In further robustness analyses, following research by Malmendier and Nagel (2016), who show that experience of economic crises has long-lasting effects on expectations, and Goldfayn-Frank and Wohlfart (2020), who show that Germans who lived in the German Democratic Republic hold different inflation expectations than Germans who did not, we analyze whether ­experience of economic turbulence during transition affects expectations. We do not find that memories of hyperinflation or memories of banking crises have a significant effect on expectations of euro area accession.

5 Conclusions

We first describe the distribution of expectations and show how it has changed during the sample period. We find that, in general, the time horizons until expected euro adoption in the countries under review have tended to lengthen with the passage of time, and uncertainty appears to have played a substantial and, over time, increasing role in the formation of these expectations. More specifically, we also explore rounding behavior as an expression of uncertainty. Rounding behavior is of interest because, together with limitations of knowledge about euro area accession, it relates to the phenomenon of expectations that are not in line with the institutional framework that governs the adoption of the euro (i.e. expectations that the euro could be introduced before the earliest technically feasible point in time).

In the second part of the paper we focus on how (de facto) euroization as well as differences in monetary policy regimes and institutions affect expectations. Based on multinomial logit models, we substantiate that the exposure of individuals to features of de facto euroization has an impact on euro adoption expectations. Exposure to euroization tends to increase the likelihood of more optimistic euro adoption expectations and lowers the likelihood of “don’t know” answers. In a similar vein, trust in institutions (national central bank, EU) and in the stability of currencies (euro, local currency) is associated with a higher likelihood of more optimistic euro introduction expectations. Both main results broadly hold – with some heterogeneity – for both CESEE EU member states and CPCs.

In policy terms, we would offer the following takeaways and implications: First, a successful promotion of the use of local currencies (de-euroization strategies, as applied e.g. in Serbia and Albania) could have some effect on euro adoption expectations going forward (e.g. dampen expectations of a swift euro introduction). Second, our results reinforce the notion that trust and stable monetary expectations are key for the formation of euro adoption expectations. Third, improving the knowledge about the framework of euro adoption might help reduce the share of overly optimistic expectations as regards euro adoption. In turn, this might help to improve the quality of financial decisions taken by individuals. Fourth, the same could hold true for policies that reduce uncertainty with respect to future euro adoption, including a clear and time-consistent communication on these issues, as witnessed in recent years in Croatia. At the same time, a note of caution needs to be added here: The large heterogeneity across countries which we document in this study needs to be considered when designing policies. What works in one country, may not necessarily work in another.

Our study has intentionally focused on a rather narrow research question but also points to several possible future avenues of research. Beyond distance to the euro area, are there regional heterogeneities such as local economic development that affect expectations of accession to the euro area? Inspired by research on inflation expectations (e.g. D’Acunto et al., 2019), interesting research questions for the future might also include: What is the role of cognitive abilities and financial literacy for the formation of euro introduction expectations and how does literacy affect uncertainty? How do individual attitudes and beliefs, including political attitudes as well as personal preferences for introduction affect expectations? The fall 2020 wave of the OeNB Euro Survey will include survey questions designed to address some of these issues. In addition, future research may look at the relationship of changing expectations on households’ investment and saving behavior in more detail.

References

Allinger, K. 2018. Croatia on the road to euro adoption: Assessing the recent literature on ­exchange rate misalignments. In: OeNB Konjunktur aktuell. June. 34–38.

Backé, P. and S. Dvorsky. 2018. Enlargement of the euro area toward CESEE: progress and perspectives. In: Focus on European Economic Integration Q3/18. OeNB. 43–56.

Backé, P., I. Korhonen, D. Ritzberger-Grünwald and L. Solanko. 2019. A tribute to 30 years of transition in CESEE. In: Focus on European Economic Integration Q3/19. OeNB. 11–28.

Backé, P., C. Thimann, O. Arratibel, O. Calvo-Gonzalez, A. Mehl and C. Nerlich. 2004. The acceding countries’ strategies towards ERM II and the adoption of the euro: an analytical review. European Central Bank Occasional Paper Series No. 10.

Ben-David, I., E. Fermand, C. M. Kuhnen and G. Li. 2018. Expectations Uncertainty and Household Economic Behavior. NBER Working Paper No. 25336.

Binder, C. C. 2017. Measuring uncertainty based on rounding: New method and application to inflation expectations. In: Journal of Monetary Economics 90. 1–12.

Brown, M. and H. Stix. 2015. The euroization of bank deposits in Eastern Europe. In: Economic Policy 30(81). 95–139.

Bryan, M. F. and G. Ventaku. 2001a. The demographics of inflation opinion surveys. Federal Reserve Bank of Cleveland, Economic Commentary, 10.15.2001.

Bryan, M. F. and G. Ventaku. 2001b. The curiously different inflation perspectives of men and women. Federal Reserve Bank of Cleveland, Economic Commentary, 11.01.2001.

Christelis, D., D. Georgarakos, T. Jappelli and M. van Rooij. 2020. Trust in the central bank and inflation expectations. International Journal of Central Banking (forthcoming).

D’Acunto, F., D. Hoang, M. Paloviita and M. Weber. 2019. Cognitive abilities and inflation expectations. In: AEA Papers and Proceedings 109. 562–566.

Deutsche Bundesbank. 2019. The relevance of surveys of expectations for the Deutsche Bundes­bank. In: Monthly Report December 2019. Deutsche Bundesbank. 53–71.

Dovern, J. 2020. Eliciting expectation uncertainty from private households (mimeo).

Easaw, J., R. Golinelli and M. Malgarini. 2013. What determines households inflation expectations? Theory and evidence from a household survey. European Economic Review 61. 1–13.

European Central Bank. 2003. Policy position of the Governing Council of the European Central Bank on exchange rate issues relating to acceding countries. 18 December.

European Central Bank. 2019. 18th annual review on the international role of the euro.
https://www.ecb.europa.eu/pub/ire/html/ecb.ire201906~f0da2b823e.en.html

European Central Bank. 2020a. The Bulgarian lev and the Croatian kuna in the exchange rate mechanism (ERM II). Published as box in the ECB Economic Bulletin, Issue 6. https://www.ecb.europa.eu/pub/economic-bulletin/focus/2020/html/ecb.ebbox202006_01~db5e37768d.en.html

European Central Bank. 2020b. Consumer Expectations Survey. https://www.ecb.europa.eu/stats/ecb_surveys/consumer_exp_survey/html/index.en.html

European Commission. 2020. Flash Barometer 487. Introduction of the euro in the member states that have not yet adopted the common currency. https://ec.europa.eu/commfrontoffice/publicopinion/index.cfm/survey/getsurveydetail/instruments/flash/surveyky/2261

Fidrmuc, J., M. Hake and H. Stix. 2013. Households’ foreign currency borrowing in Central and Eastern Europe. In: Journal of Banking & Finance 37(6). 1880–1897.

Goldfayn-Frank, O. and J. Wohlfart. 2020. Expectation formation in a new environment: Evidence from the German Reunification. Journal of Monetary Economics.

Ize, A. and E. Levy Yeyati. 2003. Financial dollarization. In: Journal of International Economics 59(2). 323–347.

Jeanne, O. 2005. Why do emerging economies borrow in foreign currency? In: Eichengreen,
B. and R. Hausmann (eds.). Other People’s Money: Debt denomination and financial instability in emerging market economies. University of Chicago Press. 190–217.

Krüger, F. and L. Pavlova. 2020. Quantifying subjective uncertainty in survey expectations (mimeo).

Malmendier, U. and S. Nagel. 2016. Learning from Inflation Experiences. In: The Quarterly Journal of Economics 131(1). 53–87.

Manski, C.F. 2004. Measuring expectations. Econometrica 5, 1329–1376.

Manski, C.F. and F. Molinari. 2010. Rounding probabilistic expectations in surveys. In: Journal of Business Economics and Statistics 28(2). 219–231.

Mellina, S. and T. Schmidt. 2018. The role of central bank knowledge and trust for the public’s inflation expectations. Discussion Papers 32/2018. Deutsche Bundesbank.

Rondinelli, C. and R. Zizza. 2020. Spend today or spend tomorrow? The role of inflation ­expectations in consumer behavior. Bank of Italy Temi di Discussione (Working Paper) No. 1276.

Scheiber, T. 2019a. Use of euro cash in CESEE countries. In: European Central Bank. The international role of the euro. Box 5. June 2019. 35–37.

Scheiber, T. 2019b. The use of euro cash in CESEE and the role of euro adoption expectations. In: Focus on European Economic Integration Q3/19. OeNB. 76–94.

Stix, H. 2013. Why do people save in cash? Distrust, Memories of Banking Crises, Weak Institutions and Dollarization. In: Journal of Banking and Finance 37(11). 4087–4106.

Van der Klaauw, W., W. Bruine de Bruin, G. Topa, S. Potter and M. Bryan. 2008. ­
Rethinking the measurement of household inflation expectations. Preliminary findings. Federal Reserve Bank of New York Staff Report No. 359.

Annex

Table A1: Variable definitions  

Variable name	Definition
common to hold euro cash	Dummy variable based on the following question: “Please tell me whether you agree with the following statement on a scale from 1 (strongly agree) to 6 (strongly disagree): In [MY COUNTRY] it is very ­common to hold euro cash.” Answers 1 to 3 are coded as 1, else as zero.
common to have foreign currency deposits	Dummy variable based on the following question: “Please tell me whether you agree with the following statement on a scale from 1 (strongly agree) to 6 (strongly disagree): In [MY COUNTRY] it is very ­common to hold foreign currency deposits.” Answers 1 to 3 are coded as 1, else as zero.
has foreign / local currency / no deposits	Dummy variable that takes the value 1 if the respondent has deposits denominated in foreign / local currency or no deposits, else zero. Base category: Respondents who refuse to answer.
has foreign / local currency loan	Dummy variable that takes the value 1 if the respondent has a loan denominated in foreign / local currency, else zero. Base category: Respondents who do not have a loan.
receives remittances	Dummy variable that takes the value 1 if the respondent receives remittances from abroad, else zero.
regular income in euro	Dummy variable that takes the value 1 if the respondent receives regular income in euro, else zero.
LC future stable	Dummy variable based on the following question: “Please tell me whether you agree with the following statement on a scale from 1 (strongly agree) to 6 (strongly disagree): Over the next five years, the [LOCAL CURRENCY] will be very stable and trustworthy.” Answers 1 to 3 are coded as 1, else as zero.
EUR future stable	Dummy variable based on the following question: “Please tell me whether you agree with the following statement on a scale from 1 (strongly agree) to 6 (strongly disagree): Over the next five years, the euro will be very stable and trustworthy.” Answers 1 to 3 are coded as 1, else as zero.
trust in central bank, trust in EU	Dummy variable based on the following question: “Please tell me how much trust you have in the following institutions: (…) The European Union (…) the national central bank. For each of the institutions, please tell me if you tend to trust it or tend not to trust it. 1 means ‘I trust completely,’ 2 means ‘I somewhat trust,’ 3 means ‘I neither trust nor distrust,’ 4 means ‘I somewhat distrust’ and 5 means ‘I do not trust at all.’ ” Answers 1 and 2 are coded as 1, else zero.
expect depreciation	Dummy variable based on the following question: “How do you think will the exchange rate of the [LOCAL CURRENCY] against the euro develop over the next five years?” The answer “The local curreny will lose value” is coded as 1, answers “The exchange rate will stay the same” and “The local currency will gain value” are coded as zero.
expect inflation	Dummy variable based on the following question: “Please tell me whether you agree with the following statement on a scale from 1 (strongly agree) to 6 (strongly disagree): Over the next year, prices will strongly increase in [MY COUNTRY].” Answers 1 to 3 are coded as 1, else as zero.
Source: OeNB Euro Survey.

Table A2: How do sociodemographic heterogeneities affect expectations of euro introduction?  

	Respondents expect euro introduction…
Dependent variable outcome category	Before theoretically possible	Within 10 years	Within 20 years	In more than 20 years	Never	Don’t know
female	–0.001	–0.015***	–0.017***	–0.004***	–0.017***	0.054***
	(0.004)	(0.004)	(0.003)	(0.002)	(0.004)	(0.006)
age	–0.001***	0.000	0.000	–0.000***	0.001**	0.001**
	(0.000)	(0.000)	(0.000)	(0.000)	(0.000)	(0.000)
married	0.014**	–0.004	–0.001	–0.003	–0.014**	0.008
	(0.006)	(0.005)	(0.004)	(0.002)	(0.007)	(0.008)
1 person household	0.011	–0.011*	–0.01	–0.003	–0.015**	0.028***
	(0.009)	(0.007)	(0.007)	(0.004)	(0.007)	(0.010)
3+ person household	0.016***	0.001	–0.002	–0.004	–0.023***	0.011
	(0.006)	(0.003)	(0.004)	(0.003)	(0.006)	(0.007)
education: secondary	0.038**	0.027***	0.006	0.005	–0.007	–0.070***
	(0.015)	(0.007)	(0.006)	(0.004)	(0.008)	(0.012)
education: tertiary	0.060***	0.053***	0.007	0.007	–0.027**	–0.100***
	(0.016)	(0.008)	(0.007)	(0.006)	(0.011)	(0.017)
income: refused answer	–0.053***	–0.026***	–0.023***	–0.009***	0.009	0.102***
	(0.010)	(0.007)	(0.005)	(0.002)	(0.009)	(0.011)
income: medium	0.008	0.020***	0.008*	0.000	–0.011*	–0.025***
	(0.007)	(0.007)	(0.004)	(0.003)	(0.007)	(0.008)
income: high	0.015	0.039***	0.005	0.001	–0.022***	–0.039***
	(0.009)	(0.007)	(0.006)	(0.003)	(0.007)	(0.009)
retired	–0.006	–0.004	–0.004	–0.001	–0.015*	0.030***
	(0.008)	(0.008)	(0.007)	(0.004)	(0.008)	(0.010)
unemployed	0.007	–0.013*	–0.012**	0.001	0.006	0.011
	(0.007)	(0.007)	(0.004)	(0.002)	(0.010)	(0.010)
student	0.023**	0.005	0.009	0.003	–0.043***	0.002
	(0.011)	(0.012)	(0.009)	(0.004)	(0.014)	(0.013)
self-employed	0.004	0.015***	–0.006	0.003	–0.004	–0.012
	(0.013)	(0.005)	(0.007)	(0.003)	(0.009)	(0.013)
N	39,536	39,536	39,536	39,536	39,536	39,536
Log-L	–54,431	–54,431	–54,431	–54,431	–54,431	–54,431
country and wave fixed effects	Yes	Yes	Yes	Yes	Yes	Yes
Source: OeNB Euro Survey (2014−2019). Authors’ calculations.
Note: Multinomial logit results, average marginal effects reported. Standard errors, in parentheses, are clustered at the country-wave level. The Wald test for combining dependent categories is significant for all outcomes of the dependent variable at the 1% level.

Table A3: Robustness analysis: How significant is exposure to euroization and the euro area for expectations?  

	Respondents expect euro introduction...
Dependent variable outcome category	Before theoretically possible	Within 10 years	Within 20 years	In more than 20 years	Never	Don’t know
common to hold euro cash	0.022***	0.019***	–0.003	–0.006*	–0.005	–0.028***
	(0.008)	(0.007)	(0.005)	(0.003)	(0.008)	(0.008)
common to have foreign currency deposits	0.022**	0.001	0.008*	0.000	–0.035***	0.004
	(0.009)	(0.006)	(0.005)	(0.003)	(0.011)	(0.009)
has foreign currency deposits	0.038**	0.032***	0.011	0.000	–0.028*	–0.053***
	(0.018)	(0.007)	(0.014)	(0.005)	(0.014)	(0.012)
has local currency deposits	0.011	0.022***	0.016***	–0.001	–0.026***	–0.023*
	(0.013)	(0.006)	(0.006)	(0.006)	(0.009)	(0.013)
has local currency loan	0.005	0.011*	–0.003	–0.001	–0.012	–0.001
	(0.008)	(0.007)	(0.005)	(0.003)	(0.009)	(0.009)
has foreign currency loan	–0.004	–0.009	0.011	0.007	0.009	–0.013
	(0.010)	(0.007)	(0.007)	(0.005)	(0.011)	(0.011)
receives remittances	–0.01	0.009	0.007	0.009**	0.001	–0.016*
	(0.014)	(0.006)	(0.006)	(0.004)	(0.016)	(0.009)
regular income in euro	0.004	0.016	0.004	–0.005	–0.006	–0.013
	(0.014)	(0.011)	(0.008)	(0.006)	(0.014)	(0.020)
EU member state (0/1)	–0.044	0.316***	–0.079***	–0.044***	–0.241***	0.092*
	(0.029)	(0.070)	(0.011)	(0.016)	(0.029)	(0.055)
N	32,571	32,571	32,571	32,571	32,571	32,571
Log-L	–45,781	–45,781	–45,781	–45,781	–45,781	–45,781
country and wave fixed effects	Yes	Yes	Yes	Yes	Yes	Yes
sociodemographic control variables	Yes	Yes	Yes	Yes	Yes	Yes
Source: OeNB Euro Survey (2014−2019). Authors’ calculations.
Note: Multinomial logit results, average marginal effects reported. Further sociodemographic controls are included but not reported. Standard errors, in parentheses, are clustered at the country-wave level. The Wald test for combining dependent categories is significant for all outcomes of the dependent variable at the 1% level.

Table A4: Robustness analysis: How significant are monetary expectations and trust in institutions for expectations?  

	Respondents expect euro introduction…
Dependent variable outcome category	Before theoretically possible	Within 10 years	Within 20 years	In more than 20 years	Never	Don’t know
LC future stable	0.001	0.018***	0.013**	–0.001	–0.01	–0.020***
	(0.008)	(0.007)	(0.005)	(0.003)	(0.010)	(0.007)
EUR future stable	0.029***	0.022***	–0.007	–0.004	–0.050***	0.01
	(0.009)	(0.007)	(0.005)	(0.004)	(0.010)	(0.009)
trust in central bank	0.037***	0.024***	–0.001	–0.010***	–0.040***	–0.01
	(0.010)	(0.008)	(0.006)	(0.003)	(0.009)	(0.010)
trust in EU	0.049***	0.028***	0.001	–0.004	–0.076***	0.001
	(0.010)	(0.006)	(0.005)	(0.004)	(0.009)	(0.008)
expect depreciation	0.022**	–0.005	–0.006	–0.001	0.009	–0.018**
	(0.008)	(0.006)	(0.005)	(0.003)	(0.009)	(0.009)
expect inflation	–0.022*	–0.006	0.009*	0.009***	0.018*	–0.006
	(0.013)	(0.005)	(0.005)	(0.003)	(0.010)	(0.008)
EU member state (0/1)	–0.070**	0.331***	–0.072***	–0.045***	–0.238***	0.095
	(0.029)	(0.069)	(0.012)	(0.015)	(0.028)	(0.058)
N	29,010	29,010	29,010	29,010	29,010	29,010
Log-L	–40,786	–40,786	–40,786	–40,786	–40,786	–40,786
country and wave fixed effects	Yes	Yes	Yes	Yes	Yes	Yes
sociodemographic control variables	Yes	Yes	Yes	Yes	Yes	Yes
Source: OeNB Euro Survey (2014−2019). Authors’ calculation.
Note: Multinomial logit results, average marginal effects reported. Further sociodemographic controls are included but not reported. Standard errors, in parentheses, are clustered at the country-wave level. The Wald test for combining dependent categories is significant for all outcomes of the dependent variable at the 1% level.