COVID-19 Dashboard of Economic Indicators...2021/01/27 · L’évolution des opportunités d’emplois suit les mesures de (dé)confinement (moyenne mensuelle des offres d’emplois

COVID-19 Dashboardof Economic Indicators

27 January 2021

2

COVID-19 in België

Evolutie van het aantal opnames in het ziekenhuis

629

879

89266

5759

7487

1958

0

1000

2000

3000

4000

5000

6000

7000

8000

9000

0

100

200

300

400

500

600

700

800

90015

/03/

2020

22/0

3/20

2029

/03/

2020

05/0

4/20

2012

/04/

2020

19/0

4/20

2026

/04/

2020

03/0

5/20

2010

/05/

2020

17/0

5/20

2024

/05/

2020

31/0

5/20

2007

/06/

2020

14/0

6/20

2021

/06/

2020

28/0

6/20

2005

/07/

2020

12/0

7/20

2019

/07/

2020

26/0

7/20

2002

/08/

2020

09/0

8/20

2016

/08/

2020

23/0

8/20

2030

/08/

2020

06/0

9/20

2013

/09/

2020

20/0

9/20

2027

/09/

2020

04/1

0/20

2011

/10/

2020

18/1

0/20

2025

/10/

2020

01/1

1/20

2008

/11/

2020

15/1

1/20

2022

/11/

2020

29/1

1/20

2006

/12/

2020

13/1

2/20

2020

/12/

2020

27/1

2/20

2003

/01/

2021

10/0

1/20

2117

/01/

2021

24/0

1/20

21

Aantal nieuwe opnames (linkeras) Totaal aantal patiënten in het ziekenhuis (rechteras)

3Bron: Sciensano, Belgisch Instituut voor de Volksgezondheid: 26 januari 2021.https://epidemio.wiv-isp.be/ID/Documents/Covid19/Meest recente update.pdf

1. COVID-19 in België: aantal gehospitaliseerde patiënten daalttraag en bevindt zich nog steeds op een veel te hoog niveau

https://epidemio.wiv-isp.be/ID/Documents/Covid19/Meest%20recente%20update.pdf

4

GDP and confidence indicatorsfor Belgium

70

75

80

85

90

95

100

105

110

Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4

2019 2020 2021 2022 2023

December 2020 projections p.m. June 2020 projections p.m. Scenario without COVID-19

5

The Belgian economy is expected to return to its pre-crisis level at theend of 2022, but it will remain below the scenario without COVID-19

Real GDP in Belgium(quarterly data, index 2019Q4=100, annual growth rates in the top boxes)

1,7 % -6,7 % 3,5 % 3,1 % 2,3 %

P R O J E C T I O N S

Sources: National Accounts Institute (NAI), National Bank of Belgium (NBB).

6

Het ondernemersvertrouwen stijgt lichtjes verder en benadert zijnlangetermijngemiddelde

-32

-11 (maart)

-36 (april)-34 (mei)

-8 (januari 2021)

-40

-30

-20

-10

0

10

20

2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021

Brutoreeks Langetermijngemiddelde sinds 1985 Afgevlakte reeks

Algemene synthetische curve

Bron: Nationale Bank van België (NBB), laatst beschikbare gegevens: 25 januari 2020, perscommuniqué maandelijkse conjunctuurenquête bij de bedrijven.

https://www.nbb.be/doc/dq/n/dq3/histo/pnc2101.pdf

Baromètre de conjoncture – Belgique : Branches d’activité – janvier 2021

La conjoncture s’est renforcée en janvier dans la construction et dansles services

7Moyenne de long terme (depuis 1980)Série dessaisonalisée et lissée Série dessaisonalisée

-70-60-50-40-30-20-10

01020

2015 2016 2017 2018 2019 2020 2021

Industrie manufacturière

CommerceConstruction

Services aux entreprises

-70-60-50-40-30-20-10

01020

2015 2016 2017 2018 2019 2020 2021

-70-60-50-40-30-20-10

01020

2015 2016 2017 2018 2019 2020 2021

-70-60-50-40-30-20-10

01020

2015 2016 2017 2018 2019 2020 2021

Source: Banque nationale de Belgique (BNB), dernières données disponibles: janvier 2021.

8

Het consumentenvertrouwen gaat er wat op achteruit, na deforse verbetering vorige maand

-9 (mrt)

-26

-10 (jan)

-35

-30

-25

-20

-15

-10

-5

0

5

10

15

2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021

Consumentenvertrouwen Langetermijngemiddelde sinds 1985

Historisch minimum

Bron: NBB, laatst beschikbare gegevens: 21 januari 2021, perscommuniqué maandelijkse consumentenenquête.

https://www.nbb.be/doc/dq/n/dq3/histo/pne2101.pdf

12 14 13 9 11 12 1720 17 13 15 19

17 16 15 15 16 1423 24 21

21 2518

20 17 17 18 15 16

30 20 22 25 2128

51 52 55 59 59 58

30 36 39 41 39 35

0

20

40

60

80

100

Aug Sep Oct Nov Dec Jan Aug Sep Oct Nov Dec Jan

Total Households with losses > 10%²Less than 1 month 1 - 3 months4 - 6 months More than 6 months

9Source: NBB, replies to January 2021 consumer survey (additional COVID-19 questions).1 Households with losses >10% (16 %) and less than three months savings (37 %) = 6 % of the total of households.2 16 % of total respondents.

How long can you cover your expensesthrough a savings buffer?(in % of the 1 850 respondents, unless otherwise stated)

Is your household sufferinga loss of income?(in % of 1 850 respondents)

Around 16 % of households suffer an income loss of more than 10 %and 37 % of them have a savings buffer of less than 3 months1

Yes:More than >10 %:

16 %

70 71 72 71 74 77

9 9 8 8 97

13 12 12 13 10 95 4 5 5 4 53 4

2 4 3 3

0

20

40

60

80

100

Aug Sep Oct Nov Dec Jan

No losses < 10% 10-30%

30-50% >50%

No losses: 77 %A large majority ofBelgian householdshas been unaffected

(so far)

0

20

40

60

80

100O

ct

Nov De

c

Jan

Oct

Nov De

c

Jan

Oct

Nov De

c

Jan

Oct

Nov De

c

Jan

Belgium (1850respondents)

Flanders (750respondents)

Wallonie (750respondents)

Brussels (350respondents)

No losses < 10% 10 - 30 % 30 - 50% > 50%

10

Savings buffer remains higher in Flanders(in % of respondents with loss of income)

In January, the proportion of households sufferingno loss of income increases in all regions(in % of respondents)

Flemish households still hold the less defavourable position(especially regarding savings buffer)

25252224

16 12 13 16 9 9 1217 19 15 11 14

2611 17

19

2119 23 18 20 15

19 1524

21 24 2116

22

29 19

2124 19 24

15 1616 16

2628

22 2928

28

2127

42 45 45 4156 59 54 52

31 3543 36

3139 33 34

0

20

40

60

80

100

Oct

Nov De

c

Jan

Oct

Nov De

c

Jan

Oct

Nov De

c

Jan

Oct

Nov De

c

Jan

Belgium Flanders Wallonie Brussels

Less than 1 month 1 - 3 months4 - 6 months More than 6 months

Source: NBB, replies to January 2021 consumer survey (additional COVID-19 questions).

0

50

100

150

200

250

300

350

400

2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020

11Source: Algaba, A., Borms, S., Boudt, K. & Van Pelt, J. (2020). The Economic Policy Uncertainty index for Flanders, Wallonia and Belgium. Research note. doi: 10.2139/ssrn.3580000.The index reflects normalized frequency counts of news articles related to economic policy uncertainty, latest available data: December 2020.

Economic Policy Uncertainty index for Belgium(monthly indicator)

Economic policy uncertainty has eased recently, but remains elevated

Belgian governmentformation

April 2020: COVID-19

Belgian government fallsover UN Migration Pact

European debt crisis

Global financial crisis

12

Labour market

13Source: Institut des Comptes Nationaux (ICN), dernières données disponibles: troisième trimestre 2020.

L’emploi salarié plus durement impacté que l’emploi indépendant(emploi en personnes - variation trimestrielle en %)

0,50,4 0,4 0,4

-0,2

-0,8

0,2

-1,2

-1,0

-0,8

-0,6

-0,4

-0,2

0,0

0,2

0,4

0,6

0,8

2019-T1 2019-T2 2019-T3 2019-T4 2020-T1 2020-T2 2020-T3

Indépendants Salariés Emploi total

0,11

-0,46

0,05

-0,05

0,42

-0,70

0,94

0,08

0,15

-0,13

0,15

0,18

-0,38

-0,09

-1,67

-0,36

-0,480,05

-1,76

0,18

-0,56

-0,77

-2,0 -1,5 -1,0 -0,5 0,0 0,5 1,0 1,5

Agriculture

Industry

Construction

Trade, hotels and restaurants, transport

Information and communication

Financial activities

Property business

Business services

Administration and education

Health and social services

Other services

Total employment

2020 Q2 2020 Q3Source: NAI, latest available data: third quarter 2020.

14

Impact on employment stronger for some branches of activity(QoQ variation in %)

pm thousandsof people

4 880

213

654

855

975

30

113

129

1 000

291

560

60

15Source: Federgon, dernières données disponibles: novembre 2020.

Chute brutale du travail intérimaire en avril, reprise partielle par après(données mensuelles, en milliers d’heures)

350

400

450

500

550

600

650

700

750

800

2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020

16Sources: Actiris, Forem, VDAB, dernières données disponibles: décembre 2020.

VDABActiris

L’évolution des opportunités d’emplois suit les mesures de(dé)confinement(moyenne mensuelle des offres d’emplois reçues par les services publics de l’emploi régionaux via le circuit ordinaire)

Forem

0

500

1 000

1 500

2 000

2 500

3 00020

20 M

120

20 M

220

20 M

320

20 M

420

20 M

520

20 M

620

20 M

720

20 M

820

20 M

920

20 M

1020

20 M

1120

20 M

12

2019

2020

0

5 000

10 000

15 000

20 000

25 000

30 000

2020

M1

2020

M2

2020

M3

2020

M4

2020

M5

2020

M6

2020

M7

2020

M8

2020

M9

2020

M10

2020

M11

2020

M12

2019

2020

0

1 000

2 000

3 000

4 000

5 000

6 000

7 000

8 000

2020

M1

2020

M2

2020

M3

2020

M4

2020

M5

2020

M6

2020

M7

2020

M8

2020

M9

2020

M10

2020

M11

2020

M12

2019

2020

17Source: Federgon, dernières données disponibles (séries dessaisonalisées): décembre 2020.

Les prévisions d’emplois issues des enquêtes de conjonctureégalement(données désaisonnalisées et lissées)

-50

-40

-30

-20

-10

0

10

20

30

40

2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020

IndustrieConstruction (gros œuvre de bâtiments)CommerceServices aux entreprises

Série dessaisonalisée et lissée Série dessaisonalisée

Mass redundancy procedures: above 2019 average(workers concerned)

18

0

500

1 000

1 500

2 000

2 500

Janu

ary

Febr

uary

Mar

ch

April

May

June July

Augu

st

Sept

embe

r

Oct

ober

Nov

embe

r

Dece

mbe

r

2020 2021 pm monthly average 2019

Source: Federal Public Service Employment, Labour and Social Dialogue (FPS ELSD), latest data available: 22 January 2021.

19Source: NEO, latest available data: November 2020.

Annual variation(monthly data, thousands of people)

Limited rise in unemployment for the time being …

-60

-40

-20

0

20

40

60

80

2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020

Flanders Wallonia Brussels Belgium

◆ Peak observed in May: +38 000, situation in November: +22 000

20

… concentrated on men and medium and highly-educated peopleAnnual variation(monthly data)

-20-15-10-505

1015202530

Men

Wom

en

Less

than

6 m

onth

s

6-12

mon

ths

1 yea

r and

mor

e

Youn

ger t

han

20

20-3

0 ye

ars

30-5

0 ye

ars

50 a

nd o

lder

Low-

educ

ated

Med

ium

-edu

cate

d

High

ly-ed

ucat

ed

In thousands of people In %

Source: NEO, latest available data: December 2020.

21Source: NAI, NEO, NBB, latest available data: December 2020.

Temporary unemployment: following lockdown measures

93429%

1 15537%

92229%

56218%

34111%

31110%

2438%

35711%

39313%

1 033

1 233

986

615

410331 281

423518

386

0

200

400

600

800

1 000

1 200

1 400

March April May June July August September October November December

Payments pm Employer's request (DRS) pm highest level recorded during the financial crisis

Average number of days per worker

March April May June July August September October November8.8 15.8 10.9 9.4 8.3 8.3 8.6 8.2 10.6

Monthly effective use and access demands(payments linked to COVID-19, thousands of people and % of private salaried employment, p.m. DRS linked to COVID-19, thousands of people,monthly data)

22Source: Federal Public Service Social Security, confidential data, NAI, NBB, latest available data: December 2020.1 Data related to payments.

Bridging right, provisional data1(thousands of people and % of self-employed in principal activity)

Self-employed: unprecedent use of financial support

396(48 %)

414(50 %) 379

(46 %)

144(17 %) 121

(15 %)119

(14 %) 85(10 %)

108(13 %)

151(18 %)

105(13 %)

0

50

100

150

200

250

300

350

400

450

500

March April May June July August September October November December

Before the crisis, about 90 self-employed benefited of the bridging right.At the peak of the crisis, in April, they were 414 000.

64

65

66

67

68

69

70

71

72

2016

T120

16T2

2016

T320

16T4

2017

T120

17T2

2017

T320

17T4

2018

T120

18T2

2018

T320

18T4

2019

T120

19T2

2019

T320

19T4

2020

T120

20T2

2020

T3

2020

M10

e20

20M

11 e

Trimestriel Mensuel

23Source: Statbel, dernières données disponibles: en trimestriel: 3ème trimestre - en mensuel: novembre 2020.1 Les indicateurs mensuels sont sujets à de plus fortes fluctuations aléatoires que les résultats trimestriels et annuels car ils reposent sur un douzième de l’échantillon annuel. Les variations d’une

période à l’autre doivent être interprétés avec prudence.

Taux de chômage(15-64)

Taux d’emploi(20-64)

La crise sanitaire a interrompu une dynamique positive(taux harmonisés issus des enquêtes force de travail1)

0

1

2

3

4

5

6

7

8

9

2016

T120

16T2

2016

T320

16T4

2017

T120

17T2

2017

T320

17T4

2018

T120

18T2

2018

T320

18T4

2019

T120

19T2

2019

T320

19T4

2020

T120

20T2

2020

T3

2020

M10

e20

20M

11 e

24

ERMG survey

The ERMG survey has been monitoring the COVID-19 impact oncompanies and self-employed since the beginning of the crisis¹◆ Surveys conducted by (selection of) the following federations:

25

Round Period Federations Replies Comment1 23-24 March BECI, UWE, VOKA 1 700 Results not published2 30-31 March BECI, UNIZO, UWE, VOKA 4 725 First press release3 6-7 April BECI, BOERENBOND, NSZ, UNISOC, UNIZO, UWE, VOKA 6 900 UNISOC was analysed separately4 14-15 April BECI, NSZ, UNIZO, UWE, VOKA 5 5005 20-21 April BECI, NSZ, UNIZO, UWE, VOKA 3 5286 27-28 April BECI, NSZ, UNIZO, UWE, VOKA 4 2087 5-6 May BECI, BOERENBOND, UNIZO, UWE, VOKA 2 6758 12-13 May BECI, UNIZO, UWE, VOKA 2 1859 25-27 May BECI, NSZ, UNIZO, UWE, VOKA 2 99310 8-10 June BECI, NSZ, UNIZO, UWE, VOKA 2 36511 22-24 June BECI, NSZ, UNIZO, UWE, VOKA 3 13612 17-19 August BECI, NSZ, UCM, UNIZO, UWE, VOKA 4 43013 21-23 September BECI, NSZ, UNIZO, UWE, VOKA 2 86814 19-21 October BECI, UCM, UNIZO, UWE, VOKA 5 13115 9-10 November BECI, NSZ, UCM, UNIZO, UWE, VOKA 5 63116 7-9 December BECI, UCM, UNIZO, UWE, VOKA 3 79817 11-13 January BECI, NSZ, UCM, UNIZO, UWE, VOKA 5 358

Source: ERMG survey, latest available data: 12 January 2021.¹ Note that changes over time should be interpreted with care as the companies participating to the survey and the composition of the sample can differ from one week to another.

-33 -33-36

-33 -34 -32-29 -31

-26-23

-17-13 -14 -14

-17-14 -12

-40

-30

-20

-10

0

23 M

arch

30 M

arch

6 Ap

ril

13 A

pril

20 A

pril

27 A

pril

5 M

ay

12 M

ay

26 M

ay

9 Ju

ne

23 Ju

ne

18 A

ugus

t

22 S

epte

mbe

r

20 O

ctob

er

10 N

ovem

ber

8 De

cem

ber

12 Ja

nuar

y

Recovery

26Source: ERMG survey, latest available data: 12 January 2020.¹ This approach excludes the human health industry, the public sector and firms that were identified as belonging to a miscellaneous ‘other’ industry.² 2022 revenue expectations were not asked in the survey rounds before December.

Expected impact on turnover in 2021 / 2022(in %, weighted average based on revenues and industry value added¹)

COVID-19 impact on weekly turnover(in %, weighted average based on revenues and industry value added¹)

-10 -10-11 -12-9

-6-9

-4

-40

-30

-20

-10

0

2021 2022Expectation of Survey 18 AugustExpectation of Survey 22 SeptemberExpectation of Survey 20 OctoberExpectation of Survey 10 NovemberExpectation of Survey 8 DecemberExpectation of Survey 12 January

While the current revenue loss and the outlook have further improved,the recovery is still expected to remain slow and only partial

Lockdown I StagnationLockdown

II Recovery

NA²

NA²

NA²

NA²

-100

-90

-80

-70

-60

-50

-40

-30

-20

-10

0

Arts,entertainmentand recreation

Accommodationand foodservices

Transportationand logistics

Support services Construction Wholesale Manufacturing Information andcommunication

Retail sales(non-food)

Real estateactivities

Financial andinsuranceactivities

Agriculture Retail sales(food)

March-April (Lockdown I)(Rounds 2-6)

May-June(Rounds 7-11)

August-October(Rounds 12-14)

November 10 (Lockdown II)(Round 15)

December 8(Round 16)

January 12(Round 17)

27

While stable in most industries, revenues rise in January in non-foodretail, wholesale and real estate, but partly due to temporary factors¹

Source: ERMG survey, latest available data: 12 January 2021.¹ Temporary factors in January include the high discounts at the start of the sales period and pent-up demand after the November lockdown.

COVID-19 impact on weekly turnover(in %, weighted average based on revenues)

28Source: ERMG survey, latest available data: 12 January 2021.² The results for these industries are based on only a few respondents and should therefore be interpreted with caution.

Impact of the COVID-19 crisis on company turnover by industry(in %, weighted average based on revenues)

< -50 %

0 to -10 %

-10 to -20 %

-20 to -50 %

March-April(Lockdown I)(Rounds 2-6)



November(Lockdown II)

(Round 15)December(Round 16)

January(Round 17)

Events and recreation -85 -83 -79 -77 -79 -79Accommodation and food service activities -89 -78 -49 -66 -78 -70Aviation² -51 -60 -27 -15 -85 -41Road transport (persons) -55 -57 -15 -13 -23 -20Manufacture of food products -18 -19 -9 -12 -9 -18Human Resources -35 -30 -13 -11 -19 -17Liberal professions -23 -18 -10 -12 -13 -16Manufacture of textiles, wearing apparel and shoes -61 -43 -6 -19 -10 -12Manufacture of machinery and electrical equipment -29 -24 -14 -10 -11 -12Logistics -22 -26 -11 -11 -8 -11Construction -45 -20 -10 -9 -7 -10Wholesale -49 -31 -10 -19 -15 -9Engineering services -33 -15 -19 -12 -16 -8Information and communication -20 -29 -13 -13 -4 -8Retail sales (non-food) -80 -28 -15 -51 -24 -7Real estate activities -36 -26 -15 -37 -13 -7Consultancy -17 -20 -11 -14 -9 -7Manufacture of plastic and non-metallic products -19 -19 -12 -10 -8 -7Metallurgy -23 -30 -23 -10 -6 -6Manufacture of pharmaceutical and chemical products -16 -20 -11 -8 -10 -5Financial and insurance activities -13 -11 -8 -10 -1 -5Manufacture of transport equipment² -54 -36 -12 -21 -12 -5Manufacture of wood and paper products, and printing -36 -27 -11 -14 -10 -4Agriculture and fishing -14 -14 -6 -12 -10 -3Manufacture of furniture -66 -31 -13 -7 -3 -2Retail sales (food) -4 -8 -4 -9 1 -1Manufacture of computer, electronic and optical products -28 -19 -25 -11 -5 -1

0

10

20

30

40

50

60

70

80

90

100

Accommodationand

food services





Retail sales(food)

Support services Wholesale Manufacturing Information andcommunication

Construction Agriculture Financial andinsurance activities

Revenue decline by 100% Revenue decline by 75 - 99% Revenue decline by 50 - 75% Revenue decline by 20 - 50%Revenue decline by 0 - 20% No impact on revenues Positive impact on revenues

29

In addition to cross-sectoral differences, the revenue loss of firmsalso differs strongly within each industry

Source: Round 17 of ERMG survey, latest available data: 12 January 2021.¹ The results on this slide are not weighted by the 2019 revenue. Given that for most industries, the smaller firms report a larger loss, these unweighted results represent a larger average revenue loss

compared to the average revenue loss weighted by firm size, which is shown on the previous slides.

COVID-19 impact on current turnover (survey 12 January)(in % of responding firms; unweighted¹)

-70

-60

-50

-40

-30

-20

-10

0

March- April(Lockdown I)(Rounds 2-6)



November 10(Lockdown II)(Round 15)



Self-employed 1 - 10 10 - 20 20 - 50 50 - 250 250 - 1000 > 1000

30Source: ERMG survey, latest available data: 12 January 2021.¹ Results are not stratified by industry, but the observations of Boerenbond are excluded (to avoid an overrepresentation of the agriculture industry in the sample).

Reported COVID-19 impact on weekly turnover, by number of employees(in %, unweighted average¹)

Throughout the pandemic the self-employed and smallest firmshave been suffering the greatest losses

-60

-50

-40

-30

-20

-10

0

Self-employed 1 - 10 10 - 20 20 - 50 50 - 250 250 - 1000 > 1000

Flemish Region Walloon Region Brussels-Capital Region

31Source: Round 17 of ERMG survey, latest available data: 12 January 2021.¹ Results are not stratified by industry.

Reported impact on weekly turnover by number of employees (survey 12 January)(in %, unweighted average¹)

The January revenue loss of the self-employed and the smallest firmsis larger in Wallonia and Brussels

-100

-90

-80

-70

-60

-50

-40

-30

-20

-10

0









All firms (weighted average based on revenues) Self-employed (unweighted average) 1-10 employees (unweighted average)

32

Also within each industry, average revenue losses are much larger forthe self-employed and the smallest firms

Source: ERMG survey, latest available data: 12 January 2021.

COVID-19 impact on current turnover (survey 12 January)(in %)

-100-90-80-70-60-50-40-30-20-10

0









Week of January 12 2021 expectation 2022 expectation

33

Revenues are expected to improve in 2021 and 2022 in most industriesbut a persistent loss remains, especially for the worst-hit ones

Source: Round 17 of ERMG survey, latest available data: 12 January 2021,

Expected COVID-19 impact on current turnover and on turnover in 2021 and 2022 (survey 12 January)(in %, weighted average based on revenues)

34Source: ERMG survey, latest available data: 12 January 2021.¹ Weighted average based on industry value added. Please note that there are no results for the surveys in May and June.² Liquidity problems was not included in the surveys of March and April.

Reasons for the current revenue loss(in % of responding firms¹, multiple reasons are possible)

Lack of demand and the forced closure remain the key reasons for thecurrent revenue loss, even though they are cited slightly less in January

0

10

20

30

40

50

60

Lack of demand Forced closure Social Distancing Supply chain problems Staff shortage Liquidity problems Other Not applicable:no revenue loss






NA²

5,5

6,0

6,5

7,0

7,5

March- April(Lockdown I)(Rounds 2-6)


August-October(Rounds 12-14)²

November 10(Lockdown II)(Round 15)²

December 8(Round 16)²

January 12(Round 17)²

Self-employed 1 - 10 employees >10 employees

35Source: ERMG survey, latest available data: 12 January 2021.¹ Results are not stratified by industry; the observations of Boerenbond are excluded (to avoid an overrepresentation of the agriculture industry in the sample).² The degree of concern for the smallest firms and self-employed as of August is lower when excluding companies of the federation UCM, which only participated in the surveys as of August.

Degree of concern, by number of employees(in %, unweighted average¹)

Degree of concern has further declined, but it remains elevated forthe self-employed and smallest firms

36

The average firm expects its investment to be about 20 % belownormal in 2021 and still about 10 % below normal in 2022

-60

-50

-40

-30

-20

-10

0





Wholesale andretail trade

Manufacturing Supportservices

Information andcommunication

Construction Agriculture Financial andinsuranceactivities

2021 Investment 2022 Investment Belgium² 2021 Belgium² 2022

COVID-19 impact on expected investment in 2021 and 2022 (survey 12 January)(in %, unweighted average¹)

36Source: Round 17 of ERMG survey, latest available data: 12 January 2021.¹ The unweighted average does not take into account the size of the company. Since the large firms report a smaller decrease in their investments on average, the overall decrease in investment is smaller.² Weighted average based on the industry value added.

0

10

20

30

40

50

60

70

80

No additionalfunding

Capital injectionby the owner,

family or friends

Increase inbank credit

Longerpayment terms

to suppliers

Intra-groupfinancing

Reduction ofpayment termsto customers

Capital injectionby a publicinvestmentcompany

Capital injectionby a privateinvestmentcompany

Capital injectionby another

non-financialcompany

Other

Self-employed 1 - 10 10 - 20 20 - 50 50 - 250 250 - 1000 >1000

37Source: Round 17 of ERMG survey, latest available data: 12 January 2021.¹ Results are not stratified by industry.

Additional financing sources (in addition to support measures) used since March 2020 (survey 12 Jan.)(in % of responding firms¹, who can select multiple sources; by staff size)

Additional financing sources since March differ by firm size

38

Many small firms still need additional financing in the short run andmany also expect to go bankrupt

Source: Round 17 of ERMG survey, latest available data: 12 January 2021.¹ Results are not stratified by industry..

How long can you still meet your currentfinancial obligations without having to relyon additional capital injections oradditional loans? (survey 12 January)(in % of responding firms¹, by staff size)

Do you expect bankruptcy proceedings withinthe next 6 months? (survey 12 January)(in % of responding firms¹, by staff size)

0102030405060708090

100

Self-

empl

oyed

1 - 10

10 -

20

20 -

50

50 -

250

250

- 100

0

> 10

00

0123456789

10

Self-

empl

oyed

1 - 10

10 -

20

20 -

50

50 -

250

250

- 100

0

> 10

00

Yes, within 6 monthsYes, within 3 monthsYes, within 1 monthYes, already in bankruptcy process

< 1 month1 – 3 months3 – 6 months6 - 12 months> 12 months

0

10

20

30

40

50

60

70

80

No Yes, due to revenue loss Yes, due to late payments Yes, due to insufficientcredit lines

Yes, due to delayedgovernment payments







39

One in three firms faces liquidity problems, even though this hasimproved after the deterioration in November

Source: ERMG survey, latest available data: 12 January 2021.¹ Weighted average based on the industry value added.

Do you have liquidity problems?(in % of responding firms¹, multiple answers are possible)

0

5

10

15

20

25

30

35

Belgium² Accommodationand food services





Support services Information andcommunication

Wholesale Retail sales(food)

Construction Manufacturing Agriculture Financial andinsuranceactivities

Survey August 18(Round 12)

Survey October 20(Round 14)

Survey November 10(Round 15)

Survey December 8(Round 16)

Survey January 12(Round 17)

40

Bankruptcy risk has decreased in January but remains elevated …

Source: ERMG survey, latest available data: 12 January 2021.¹ The results of the September survey were left out as the sample was not representative (small firms based in Wallonia and Brussels, which regard the risk of bankruptcy as higher, were much less

represented in that survey).² Weighted average based on the industry value added.

Firms that consider bankruptcy to be likely or highly likely¹(in % of responding firms)

0

5

10

15

20

25

30

35

40

Belgium¹ Accommodationand food services





Support services Information andcommunication

Wholesale Retail sales(food)

Construction Manufacturing Agriculture Financial andinsuranceactivities

Survey 18 August Survey 22 September Survey 20 October Survey 10 November Survey 8 December Survey 12 January

41

… and firms estimate that almost 10 % of companies in their industryare currently in a bankruptcy process or already went bankrupt

Source: ERMG survey, latest available data: 12 January 2021.¹ Weighted average based on the industry value added.

Estimate of respondents on the proportion of companies in their sector that already are currentlyin a bankruptcy process or that already went bankrupt(in %, unweighted average)

-30

-25

-20

-15

-10

-5

0

5

Belgium¹ Accommodationand foodservices



Retail sales(food)



Support services Agriculture Financial andinsuranceactivities


Wholesale Manufacturing Construction

2020 2021

42Source: Round 17 of ERMG survey, latest available data: 12 January 2021.1 Average, weighted by the number of private sector employees in the industries.

Expected change in staff size in 2020 and 2021 (survey 12 January)(in % of total staff size of the firms in the survey, excluding self-employed)

After a decline in 2020, the number of employees in the private sectoris expected to remain stable in 2021 in net terms …

-60 000

-50 000

-40 000

-30 000

-20 000

-10 000

0

10 000

20 000



Wholesale andretail trade



Agriculture Financial andinsuranceactivities


Construction Support services Manufacturing

2020 2021

43Source: Round 17 of ERMG survey, latest available data: 12 January 2021.1 Average, weighted by the number of private sector employees in the industries.

Expected change of staff size in 2020 and 2021 (survey 12 January)(in number of employees, excluding self-employed)

... as net lay-offs in 2021 in some industries can be offset by plannednet hiring in other industries

-60 000

-50 000

-40 000

-30 000

-20 000

-10 000

0

10 000

20 000

Belgium¹

44Source: ERMG survey, latest available data: 12 January 2021.¹ Average, weighted by the number of the private sector employees of the industries in the Belgian economy.

Workforce organisation over time, Belgium¹(in % of total staff size of the firms in the survey, excl. self-employed)

The number of employees in full-time telework has further increased,while the number of temporary unemployed has declined

0

20

40

60

80

10020

Apr

il

27 A

pril

5 M

ay

12 M

ay

26 M

ay

9 Ju

ne

23 Ju

ne

18 A

ugus

t

22 S

epte

mbe

r

20 O

ctob

er

10 N

ovem

ber

8 De

cem

ber

12 Ja

nuar

y

temporarily unemployed telework mix telework/workplace at workplace sick leave on leave

0

20

40

60

80

100

Acco

mm

odat

ion

and

food

serv

ices

Arts,

ent

erta

inm

ent a

ndre

crea

tion

Tran

spor

tatio

n an

d lo

gisti

cs

Reta

il sale

s (no

n-fo

od)

Who

lesa

le

Man

ufac

turin

g

Reta

il sale

s (fo

od)

Supp

ort s

ervic

es

Info

rmat

ion

and

com

mun

icatio

n

Cons

truct

ion

Real

esta

te a

ctivi

ties

Finan

cial a

nd in

sura

nce

activ

ities

Agric

ultu

re

Workforce organisation by industry (survey 12 Jan.)(in % of total staff size of the firms in the survey, excl. self-employed)

45Source: ERMG survey of 12 January 2021.¹ Weighted average based on the industry value added.

The productivity loss due to the current teleworking is traced backto different elements

0

5

10

15

20

25

30

35

40

45

Not applicable: noproductivity loss

Fewer ideas orless networking

No productiveworking

environment athome

Service is morequalitative when itis done physically

Insufficientphysical

infrastructure

Insufficientmanagement

control

Insufficient skills Insufficient digitalinfrastructure

Other

Reasons for reduced employee productivity due to teleworking in its current form (survey 12 January)(in % of responding firms (excl. firms without telework)¹; firms can select multiple reasons

46

Credit indicatorshouseholds

47Bron: NBB, laatste beschikbare gegevens: november 2020 (laatste bijwerking: 25 januari 2021).1 Andere activa bevatten vnl. verzekeringsproducten en niet-genoteerde aandelen en worden niet geraamd op maandelijkse basis.

Waardeverminderingen in 2020Q1 van de financiële activa van departiculieren hersteld tegen einde 2020 – verhoogd sparen in 2020

Financiële activa van de particulieren:transacties(in € miljard)

Financiële activa van de particulieren:revaluaties(in € miljard)

◆ In 2020Q1 veroorzaakte de sterke daling in de beurskoersen waardedalingen in de financiëleactiva van de particulieren voor 62,8 miljard euro.Door het herstel van de beurzen in 2020Q2, 2020Q3 en vooral in november zijn dewaardedalingen uit het eerste kwartaal zo goed als volledig hersteld tegen einde 2020.Negatieve prijseffecten waren beduidend hoger tijdens de financiële crisis van 2008.

◆ p.m. de totale financiële activa van de particulieren bedroegen 1 419 miljard eindseptember 2020.

-80-60-40-20

020406080

2008

2009

2010

2011

2012

2013

2014

2015

2016

2017

2018

2019

2020

e

2020

Q1

2020

Q2

2020

Q3

2020

Oct

2020

Nov

Financiële rekeningen jaarlijks (raming tot november) 2020 perkwartaal

Schatting

Andere activa¹ Deposito's Beleggingsfondsen Schuldbewijzen Genoteerde aandelen Totaal

-5

0

5

10

15

20

2019

Q1

2019

Q2

2019

Q3

2019

Q4

2020

Q1

2020

Q2

2020

Q3

2020

Okt

2020

Nov

Financiële kwartaalrekeningen Schattingen

◆ De transacties in financiële activa van de particulieren in2020Q2 tonen forse investeringen voor totaal 18,4 miljard euro,voornamelijk door de stijging van de deposito’s, illustratief voorhet “geforceerd sparen” van de gezinnen tijdens delock down. De netto-investeringen in beleggingsfondsenen vooral in genoteerde aandelen bleven ook op eenhoog niveau in 2020Q3, evenals in de maandnovember.

48Bron: Schema A, laatste beschikbare gegevens: november 2020.

Alle deposito’s(Maandelijkse nettogroei, € miljoen)

Deposito’s Belgische huishoudens(€ miljard, sector, maandelijkse gegevens)

Deposito’s van Belgische huishoudens

150

200

250

300

350

400

450jan

-15

jun-

15

nov-

15

apr-

16

sep-

16

feb-

17

jul-1

7

dec-

17

mei

-18

okt-

18

mrt-

19

aug-

19

jan-2

0

jun-

20

nov-

20

Alle deposito's Spaarboekje

-2 000

0

2 000

4 000

6 000

8 000

10 000

jan-1

9fe

b-19

mrt-

19ap

r-19

mei

-19

jun-

19ju

l-19

aug-

19se

p-19

okt-

19no

v-19

dec-

19jan

-20

feb-

20m

rt-20

apr-

20m

ei-2

0ju

n-20

jul-2

0au

g-20

sep-

20ok

t-20

nov-

20

Negatieve saldi op rekeningen / kredietkaarten

49

Negatieve saldi op rekeningen(stock, in € miljoen, maandelijkse gegevens)

Bron: Ad hoc rapportering, Febelfin, op basis van 7 banken, laatst beschikbaregegevens: 28 december 2020.Bron: Schema A, voorschotten rekening courant, laatste beschikbare gegevens: november 2020.

Aantal rekeningen “teveel in het rood”(aantal, in duizend, wekelijkse gegevens)

1 000

1 500

2 000

2 500

3 000

3 50012

/201

4

05/2

015

10/2

015

03/2

016

08/2

016

01/2

017

06/2

017

11/2

017

04/2

018

09/2

018

02/2

019

07/2

019

12/2

019

05/2

020

10/2

020

0

50

100

150

200

250

W 13

/4W

20/

4W

27/

4W

4/5

W 11

/5W

18/5

W 2

5/5

W 1/

6W

8/6

W 15

/6W

22/

6W

29/

6W

6/7

W 13

/7W

20/

7W

27/

7W

3/8

W 10

/8W

17/8

W 2

4/8

W 3

1/8

W 7

/9W

14/9

W 2

1/9

W 5

/10

W 19

/10

W 2

/11

W 16

/11

W 3

0/11

W 14

/12

W 2

8/12

Bankkredieten van Belgische huishoudens

50Bron: Schema A, laatste beschikbare gegevens: november 2020.

Groeivoet(op jaarbasis, %)

Stock(€ miljard)

150

170

190

210

230

250

270

2015 2016 2017 2018 2019 2020-3

0

3

6

9

12

15

2007

2008

2009

2010

2011

2012

2013

2014

2015

2016

2017

2018

2019

2020

Belgium Euro area

0

50

100

150

200

250

300

35020

0720

0820

0920

1020

1120

1220

1320

1420

1520

1620

1720

1820

1920

20

51Bron: Centrale voor Kredieten aan Particulieren (CKP), laatste beschikbare gegevens: 22 januari 2020

Wanbetalingsgraad(Aantal uitstaande achterstallige contracten, % van alle uitstaandecontracten in CKP/ENR)

Nieuwe leningen(geregistreerd bedrag per werkdag in CKP, in € miljoenen)

Hypotheekleningen: nieuwe leningen en wanbetalingsgraad

Gemiddelde per werkdag over de laatste 12 maandenGemiddelde per werkdag over de laatste maandGemiddelde per werkdag over de laatste 5 werkdagen

07/0

330

/03

22/0

415

/05

07/0

630

/06

23/0

715

/08

07/0

930

/09

23/1

015

/11

08/1

231

/12

0,0%

0,2%

0,4%

0,6%

0,8%

1,0%

1,2%

1,4%

2007

2008

2009

2010

2011

2012

2013

2014

2015

2016

2017

2018

2019

2020

05101520253035404550

24/0

318

/04

13/0

507

/06

02/0

727

/07

21/0

815

/09

10/1

004

/11

29/1

124

/12

18/0

1

Aantal uitstaande achterstallige contracten(dagelijkse gegevens, rechterschaal in duizenden)

Aantal uitstaande achterstallige contracten(maandelijkse gegevens, rechterschaal in duizenden)

Wanbetalingsgraad(dagelijkse gegevens, linkerschaal in %)

Wanbetalingsgraad(maandelijkse gegevens, linkerschaal in %)

07/0

330

/03

22/0

415

/05

07/0

630

/06

23/0

715

/08

07/0

930

/09

23/1

015

/11

08/1

231

/12

52Bron: CKP, laatste beschikbare gegevens: 22 januari 2021.1 Leningen en verkopen op afbetaling (uitgezonderd kredietopeningen).

Wanbetalingsgraad(Aantal uitstaande achterstallige contracten, % van alle uitstaandecontracten in CKP/ENR)

Nieuwe leningen(geregistreerd bedrag per werkdag in CKP, in € miljoenen)

Consumentenkredieten1: nieuwe leningen en wanbetalingsgraad

Gemiddelde per werkdag over de laatste 12 maandenGemiddelde per werkdag over de laatste maandGemiddelde per werkdag over de laatste 5 werkdagen

0

10

20

30

40

50

60

7020

0720

0820

0920

1020

1120

1220

1320

1420

1520

1620

1720

1820

1920

200

50.00 0

10 0.000

15 0.000

200.0 00

250.0 00

0%

2%

4%

6%

8%

10%

12%

2007

2008

2009

2010

2011

2012

2013

2014

2015

2016

2017

2018

2019

2020

0

50

100

150

200

250

24/0

323

/04

23/0

522

/06

22/0

721

/08

20/0

920

/10

19/1

119

/12

18/0

1

Aantal uitstaande achterstallige contracten(dagelijkse gegevens, rechterschaal in duizenden)

Aantal uitstaande achterstallige contracten(maandelijkse gegevens, rechterschaal in duizenden)

Wanbetalingsgraad(dagelijkse gegevens, linkerschaal in %)

Wanbetalingsgraad(maandelijkse gegevens, linkerschaal in %)

◆ Aantal consumentenleningen die genieten ofgenoten hebben van een moratorium zoalsgeregistreerd in de Centrale voor Kredieten aanParticulieren (op 17 januari)

◇ 8 247 leningen

◇ waarvan 7 991 leningen op afbetaling(0,4 % van alle leningen op afbetaling)

53Bronnen: CKP, Febelfin.

Aantal hypotheekleningen onder moratorium

Moratoria voor leningen aan gezinnen

4,4 %

0,5 %

Aantal hypotheekleningen met een lopend moratoriumwaarvan: verlenging van eerder verleende moratoria

Aantal hypotheekleningen die genieten of genoten hebben van een moratoriumzoals geregistreerd in de Centrale voor Kredieten aan Particulieren

Febelfincijfers voor de 7 grootste banken

0

20 000

40 000

60 000

80 000

100 000

120 000

140 000

160 000

03/0

510

/05

17/0

524

/05

31/0

507

/06

14/0

621

/06

28/0

605

/07

12/0

719

/07

26/0

702

/08

09/0

816

/08

23/0

830

/08

06/0

913

/09

20/0

927

/09

11/1

025

/10

08/1

122

/11

06/1

220

/12

03/0

117

/01

54Bron: Febelfin, laatste beschikbare gegevens: 11 januari 2021.

Achterstanden bij leningen aan huishoudens stabiel sinds juni

0,0

0,5

1,0

1,5

2,0

2,5

3,0

3,5

4,0

4,513

/420

/427

/4 4/5

11/5

18/5

25/5 1/6

8/6

15/6

22/6

29/6 6/7

13/7

20/7

27/7 3/8

10/8

17/8

24/8

31/8 7/9

14/9

21/9

5/10

19/1

02/

1116

/11

30/1

114

/12

28/1

211

/1

Hypothecaire leningen Consumentenkredieten

Betalingsachterstand (1-30 dagen) op hypothecaire leningen en consumentenleningen(wekelijkse gegevens, aantal leningen met een betalingsachterstand van 1-30 dagen als % van het totaal aantal leningen)

55

Credit indicatorscorporates

56Sources: ECB, NBB.

Impact of the COVID-19 crisis on lending to non-financialcorporations (NFCs)◆ Credit developments: (see next slides)

◇ While annual NFC growth of utilised loans had accelerated in March and April (in large part due todrawdowns of credit lines by multinationals), it has slowed since May.

◇ The annual growth rate of authorised (granted) credit is now lower than that observed before the pandemic◇ The annual growth rate of used credits in September and in October are influenced by a base effect due to a

large one-off transaction that took place one year earlier (only in the Central Corporate Credit Register data)◇ Monthly growth rates of utilised and authorised loans have been low since June, with some monthly growth

rates being negative◇ Loan arrears have been stable since May◇ Small or medium-sized enterprises (SMEs) have larger proportions of loans in moratorium than larger firms

◆ According to the January 2021 Bank lending survey:◇ Declining demand for loans from Belgian enterprises in 2020Q4 was driven by a fall in fixed investment and

less need for inventories and working capital. Banks expect that this trend will go on in 2021Q1◇ No change regarding tightening in credit standards, but risk perception is still higher

57Sources: ECB, NBB.

Firms perceived less favorable credit conditions◆ Belgian firms reported a slight improvement of their credit conditions in 2020Q3 compared to

2020Q2◇ Slight improvement in the assessment of the general credit conditions by firms

- Mainly due to the industry sector and large firms- From 2020, the balance of the opinions (favorable vs unfavorable) is below the historical average

◇ Small deterioration with respect to 2020Q2 regarding requirements for collateral(source: NBB survey on credit conditions)

◆ SMEs feared a significant impact on bank loan availability in 2020Q4 and 2021Q1◇ Small deterioration regarding obstacles impeding access to bank financing between April and September

2020 compared to the previous six months- Proportion of SMEs not applying for bank credit because of possible rejection, or applying for a loan but only

receiving a limited part of the amount requested, refusing credit because the cost was too high, or having theirapplication rejected = 7.2 % (against 5,9 % on average in 2017-2019 and 5.2 % from October 2019 to March 2020)

◇ But SMEs expected a sharp deterioration in availability of bank loans over the next six months(October 2020-March 2021)- Widespread across sectors(source: SAFE survey, conducted between 7 September and 16 October 2020)

58

Non-financial corporations

NFC credit growth in Belgium: slowdown after the peak in March andApril(year-on-year % changes1, up to November 2020)

Sources: European Central Bank (ECB), NBB (Balance Sheet Items), latest available data: 30 November 2020.1 Loans granted by resident MFIs to residents, including securitised loans and loans otherwise transferred.

-10

-5

0

5

10

15

20

2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020

Belgium Euro area

Reduced contribution of multinational corporations to total creditgrowth, after massive drawdowns of credit lines in March and April …

-2

0

2

4

6

8

10

2017 2018 2019 2020

Local corporations Multinational corporations¹ Total

59Sources: NBB (Central Corporate Credit Register), latest available data: 30 November 2020.1 Firms with direct investment abroad or at least partially owned by foreign investors (10 % threshold), identified by SX.

Year-on-year growth rates for utilised credit(%)

Year-on-year growth rates for authorised credit(%)

-2

0

2

4

6

8

10

2017 2018 2019 2020

-2

0

2

4

6

8

10

2017 2018 2019 2020

Up to one year (or undefined) One to two years Two to five years Over five years Total

-2

0

2

4

6

8

10

2017 2018 2019 2020

60Source: NBB (Central Corporate Credit Register), latest available data: 30 November 2020.

Decomposition of YoY used corporate creditgrowth by maturity(%)

… which also translates into a lower contribution of short-term loans

Decomposition of YoY authorized corporatecredit growth by maturity(%)

-2

-1

0

1

2020m5 2020m6 2020m7 2020m8 2020m9 2020m10 2020m11

utilised authorised

Slightly positive growth of authorised and utilised loans inNovember

61Source: NBB (Central Corporate Credit Register), latest available data: November 2020.

Monthly growth rates of loans for Novemberof previous years(in %)

Monthly growth rates of authorised andutilised loans(in %)

0

1

2

3

2017m11 2018m11 2019m11 2020m11

- 4- 2 0 2 4 6 8

10 12

Arts,

ent

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inm

ent

and

recr

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n

Hore

ca

Who

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ndre

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Real

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Cons

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Man

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Tran

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d sto

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Info

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and

com

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Supp

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Agric

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and

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es

Oth

erMar-Nov 2020 4-y avg Mar-Nov

-4-202468

1012

Arts,

ent

erta

inm

ent

and

recr

eatio

n

Hore

ca

Who

lesa

le a

ndre

tail t

rade

Real

esta

te a

ctivi

ties

Cons

truct

ion

Man

ufac

turin

g

Tran

spor

tatio

nan

d sto

rage

Info

rmat

ion

and

com

mun

icatio

n

Supp

ort s

ervic

es

Agric

ultu

re, f

ores

try

and

fishi

ngFin

ancia

l and

insu

ranc

eac

tiviti

es

Oth

er

62Source: NBB (Central Corporate Credit Register), latest available data: November 2020.Note: Sectors are ordered based on the initial fall in sales due to the crisis (greater declines from right to left). “Other” contains all other sectors in the economy.

March-November growth rates of utilisedloans(in %)

March-November growth rates of authorisedloans(in %)

Growth in authorised and utilised loans since start of crisis is belowhistorical averages for many vulnerable sectors

60

98

56

91

45

81

18

91

47

88

0

10

20

30

40

50

60

70

80

90

100

ShortTerm

LongTerm

ShortTerm

LongTerm

ShortTerm

LongTerm

ShortTerm

LongTerm

ShortTerm

LongTerm

Self-employed(1)

SMEs(2)

Corporates(3)

Public(4)

Sum of(1) to (4)= total

63

Loan developments - weeklyNFCs in weekly reporting = Self-employed + SMEs + Corporates + Public Sector Entities

Utilisation rate (=utilised/authorized)(last weekly observation, in %)

Evolution of total loans to NFCs(in %)

99,6

97,3

80

85

90

95

100

10531

/05

14/0

6

28/0

6

12/0

7

26/0

7

09/0

8

23/0

8

06/0

9

20/0

9

11/1

0

08/1

1

06/1

2

03/0

1

Authorised Utilised

Total loans to NFCs represented as an indexnormalized to 100 % by end May stock of loans

Source: NBB/Febelfin ad hoc weekly reporting, latest available data: 3 January 2021.Note: Firm classification was provided by the banks on a best effort basis. It may differ from the official firm classification.

103,3

102,0

9092949698

100102104

31/0

507

/06

14/0

621

/06

28/0

605

/07

12/0

719

/07

26/0

702

/08

09/0

816

/08

23/0

830

/08

06/0

913

/09

20/0

927

/09

11/1

025

/10

08/1

122

/11

06/1

220

/12

03/0

1

96,7

92,29092949698

100102104

31/0

507

/06

14/0

621

/06

28/0

605

/07

12/0

719

/07

26/0

702

/08

09/0

816

/08

23/0

830

/08

06/0

913

/09

20/0

927

/09

11/1

025

/10

08/1

122

/11

06/1

220

/12

03/0

1Authorised Utilised

101,1

99,5

9092949698

100102104

31/0

507

/06

14/0

621

/06

28/0

605

/07

12/0

719

/07

26/0

702

/08

09/0

816

/08

23/0

830

/08

06/0

913

/09

20/0

927

/09

11/1

025

/10

08/1

122

/11

06/1

220

/12

03/0

1

Total loans to NFCs represented as an index normalized to 100 % by end May stock of loans64

Stable loans for firms except for a decline for corporatesNFCs in weekly reporting = Self-employed + SMEs + Corporates + Public Sector Entities

Evolution of total loans to SMEsLatest observation (authorized) 83 billion EUR

Evolution of total loans to self-employedLatest observation (authorized) 23 billion EUR

103,0

102,2

9092949698

100102104

31/0

507

/06

14/0

621

/06

28/0

605

/07

12/0

719

/07

26/0

702

/08

09/0

816

/08

23/0

830

/08

06/0

913

/09

20/0

927

/09

11/1

025

/10

08/1

122

/11

06/1

220

/12

03/0

1

Total loans to public sector entitiesLatest observation (authorized) 37 billion EUR

Evolution of total loans to corporatesLatest observation (authorized) 139 billion EUR


0

200

400

600

800

1000

1200

1400

03/0

510

/05

17/0

524

/05

31/0

507

/06

14/0

621

/06

28/0

605

/07

12/0

719

/07

26/0

702

/08

09/0

816

/08

23/0

830

/08

06/0

913

/09

20/0

927

/09

11/1

025

/10

08/1

122

/11

06/1

220

/12

03/0

1

Self-employed SMEs Corporates Public

65

Number of loans in arrears or in default are not increasing (yet?)(arrears – weekly)

Number of loans in arrears or in default(in thousands of people)

Amounts in arrears or in default(in € millions)

0

5

10

15

20

25

30

35

40

45

50

03/0

510

/05

17/0

524

/05

31/0

507

/06

14/0

621

/06

28/0

605

/07

12/0

719

/07

26/0

702

/08

09/0

816

/08

23/0

830

/08

06/0

913

/09

20/0

927

/09

11/1

025

/10

08/1

122

/11

06/1

220

/12

03/0

1


The observed increase for SMEs on 20th September is due to a technical correction.The increase of arrears for the corporate segment is linked to end-of-year operational events.

4%

55%

39%

2%


8%

30%

49%

13%

66

Total loan amounts by type of counterpartyLoan amounts in moratorium by type of counterparty

SMEs are the main beneficiaries of moratorium relative to their shareof total loans(moratorium – weekly)


67

0,1

1,0

0,1

3,5

0,2

3,3

0,0 0,2 0,1

2,5

Short Term Long Term Short Term Long Term Short Term Long Term Short Term Long Term Short Term Long Term

Self-employed(1)

SMEs(2)

Corporates(3)

Public(4)

Sum of(1) to (4) = total

Long term loans are the main type of loans in moratorium(moratorium – weekly)

% of exposures in moratorium(last weekly observation)


68

Total loan amounts by type of counterpartyLoan amounts under state guarantee by type ofcounterparty

Take-up of the state guarantee - by type of counterpartyResults, taking into account only state guarantee I(weekly data)

4,21%

43,37%52,22%

0,21%



8%

30%

49%

13%

69

Bankruptcies andnew business registrations

0

100

200

300

400

500

600

700

Sep 2020 Oct 2020 Nov 2020 Dec 2020 Mid-Jan 2021(current month)

70

Source: Statbel, latest available data: 12 January 20211 Declaration of bankruptcy by the company court.2 Although the moratorium on filings for bankruptcies came to an end on 17 June 2020, the tax administration and the ONSS applied a de facto moratorium on tax and social security debts.

Other measures taken were the deferment of payment of the annual company contribution (until 31 October 2020) and the social security contributions (until 15 December 2020), and the reintroduction of a temporarysuspension of seizures. On Friday 6 November 2020, a new moratorium on bankruptcies until 31 January 2021 was approved towards businesses forced to close temporarily following the emergency measures takento limit COVID-19 and a further extension to 31 December for the payment of the annual company contribution. A new draft judicial reorganisation procedure is expected by 31 January 2021. For employersstruggling with the crisis, the ONSS agrees to an exceptional amicable payment plan with a maximum duration of 24 months for the settlement of sums due for the year 2020 (a.o. holiday pay for the 2019financial year, the 1st, 2nd, 3rd and 4th quarters of 2020). At the level of the FPS Finance, companies in difficulty as a result of the coronavirus can apply for support measures until 31 March 2021 by meansof a payment plan, exemption from interest on arrears and remission of fines for non-payment regarding several taxes..

(# by activity)Bankruptcies(# by region)

The number of bankruptcies1 decreases further in December 2020and remains far below the 2019 level …... since several provisions adopted to support businesses are still in place2

◆ About 96 % of bankruptcies are within the ‘0 to 9 workers’company size class

0

200

400

600

800

1 000

1 200

1 400

Jan2020

Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Jan2021

2020 VLA 2020 BRU 2020 WAL 2019 Belgium Transport & other servicesTradeIndustries & energy

Hotel & restaurantBuildingAgriculture & fisheries

71

(# by activity)Bankruptcies1(# by region)

2021: weekly bankruptcies figures increase since end-2020 accordingto seasonal patterns …… but remain below the 2015-19 average

0

50

100

150

200

250

300

3-9

10-16

17-2

324

-30

31 A

ug-6 7-13

14-2

021

-27

28 Se

pt-4 5-11

12-18

19-2

526

Oct-

12-

89-

1516

-22

23-2

930

Nov

-6 7-13

14-2

021

-27

28 D

ec-3 4-10

11-17

August September October November December January

VLA BRU WAL Avg 2015-19 Belgium

◆ Since August 31, the number of bankruptcies remains 35 % below the2015-19 average while in August, declared bankruptcies were close to it

0

50

100

150

200

250

300

3-9

10-16

17-2

324

-30

31 A

ug-6 7-13

14-2

021

-27

28 Se

pt-4 5-11

12-18

19-2

526

Oct-

12-

89-

1516

-22

23-2

930

Nov

-6 7-13

14-2

021

-27

28 D

ec-3 4-10

11-17

August September October November December January

Transport & other servicesTradeIndustries & energy

Hotel & restaurantBuildingAgriculture & fisheries

Source: Statbel, latest available data: 12 January 2021.1 Declaration of bankruptcy by the company court.

72

New businesses1

Business startups rise in October according to seasonal patterns… and are still higher than in 2019

0

2 000

4 000

6 000

8 000

10 000

12 000

14 000

16 000

18 000

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

VLA BRU WAL 2019 Belgium

Source: Statbel, latest available data: October 2020.1 Business creation as measured by entities registering (first registrations & re-registrations) as a VAT unit in the Crossroads Bank for Enterprises.

73

Financial markets

0

10

20

30

40

50

60

70

80

90

100

2008

2009

2010

2011

2012

2013

2014

2015

2016

2017

2018

2019

2020

2021

VIX VSTOXX

Financial markets reflect optimism, but remain at risk of setback

60

70

80

90

100

110

120

130

140

04/2

018

07/2

018

10/2

018

01/2

019

04/2

019

07/2

019

10/2

019

01/2

020

04/2

020

07/2

020

10/2

020

01/2

021

BEL 20 Euro Stoxx 50 FTSE 100 S&P 500

◆ Recent events, including the ratification of the Brexit deal, vaccine regulatory approvals, and new US government, helped unravel some of theaccumulated volatility. However, uncertainty remains over unresolved issues, such as the full impact of Brexit, new virus variants and new lockdowns,as well as sluggish vaccine rollout in some countries

◆ Confirmation of accommodative monetary stance and the prospect of new US fiscal stimulus have supported stock prices. The continueddepreciation of the dollar and encouraging US PMI data contributed to the S&P’s rally

74Source: Refinitiv, latest available data: 22 January 2021.

Major stock market indices(01/2018=100)

Implied stock market volatility(in %)

-80-60-40-20

020406080

100120140160

07/2

019

08/2

019

09/2

019

10/2

019

11/2

019

12/2

019

01/2

020

02/2

020

03/2

020

04/2

020

05/2

020

06/2

020

07/2

020

08/2

020

09/2

020

10/2

020

11/2

020

12/2

020

01/2

021

Crude Oil WTI Metals index

Copper Gold

◆ Oil price reached its highest level since the beginningof the crisis. However, prices remain extremelyvulnerable:◇ With global demand still affected by mobility

restrictions◇ Recent disagreement over production: Saudi

Arabia supported prices by pledging to cutproduction, while Russia and Kazakhstan are callingto increase production

◆ Gold price remains high in an uncertain environment,supported by weak dollar and rising inflationexpectations

◆ Prices of industrial metals have risen due to increaseddemand (partly linked to green recovery) andsupply disruptions◇ Copper trading near eight-year high

75Source: Datastream, latest available data: 22 January 2021.Note: the metals index includes aluminium, copper, lead, iron ore, tin, nickel and zinc.

Commodity price indices(01/07/2019 = 100)

Oil price recovery continues, amid disagreement within OPEC+

Corporate spreads stabilise and draw closer to their pre-crisis level

0

100

200

300

400

500

600

700

800

90007

/201

908

/201

909

/201

910

/201

911

/201

912

/201

901

/202

002

/202

003

/202

004

/202

005

/202

006

/202

007

/202

008

/202

009

/202

010

/202

011

/202

012

/202

001

/202

1US BBB Euro BBB US BB Euro BB

◆ Supportive measures by the ECB and the US Fed havehelped lower corporate yields and improved financingconditions for firms.

◆ Spreads of investment-grade corporate bonds havereturned to pre-pandemic levels.

◆ The decline in corporate spreads also reflectsinvestors’ confidence that companies will endure thepandemic.

76Source: BofA Merrill Lynch from Datastream, latest available data: 22 January 2021.

Corporate bond spreads (€ or $ denominated)(Difference vis-à-vis sovereign, basis points)

0,0

0,5

1,0

1,5

2,0

2,5

3,0

3,501

/201

803

/201

805

/201

807

/201

809

/201

811

/201

801

/201

903

/201

905

/201

907

/201

909

/201

911

/201

901

/202

003

/202

005

/202

007

/202

009

/202

011

/202

001

/202

1

Belgium Spain France Italy Netherlands

Sovereign bond spreads remain low, close to pre-pandemic levels

◆ Despite the appearance of new virus variants andreintroduction of related mobility restrictions,sovereign spreads stabilised close to their pre-crisislevels, helped by ECB’s reconfirmation of itsaccommodative monetary policy stance

◆ Recent rise in Italian spreads can be linked to marketconcerns over political uncertainty

77Source: Refinitiv, latest available data: 22 January 2021.

10-year spreads vis-à-vis Germany (EA)(%)

78

International outlook

79

Composite mobility indicator1(% change from pre-COVID-19 baseline; 7-day moving average)

Second wave: mobility less affected than in the spring

Sources: Google, Apple. Construction of mobility composite inspired by Capital Economics.1 Composite indicator is a simple average of changes in Google mobility report scores for categories “retail and recreation”, “workplaces”, and “transit stations”, and changes in Apple routing requests for

driving. Pre-COVID-19 baseline is the median value (for the corresponding day of the week) of each sub-indicator over the period January – 6 February 2020. Latest values are for 19 January 2021.

-100

-80

-60

-40

-20

0

20

4022

/02/

2020

29/0

2/20

2007

/03/

2020

14/0

3/20

2021

/03/

2020

28/0

3/20

2004

/04/

2020

11/0

4/20

2018

/04/

2020

25/0

4/20

2002

/05/

2020

09/0

5/20

2016

/05/

2020

23/0

5/20

2030

/05/

2020

06/0

6/20

2013

/06/

2020

20/0

6/20

2027

/06/

2020

04/0

7/20

2011

/07/

2020

18/0

7/20

2025

/07/

2020

01/0

8/20

2008

/08/

2020

15/0

8/20

2022

/08/

2020

29/0

8/20

2005

/09/

2020

12/0

9/20

2019

/09/

2020

26/0

9/20

2003

/10/

2020

10/1

0/20

2017

/10/

2020

24/1

0/20

2031

/10/

2020

07/1

1/20

2014

/11/

2020

21/1

1/20

2028

/11/

2020

05/1

2/20

2012

/12/

2020

19/1

2/20

2026

/12/

2020

02/0

1/20

2109

/01/

2021

16/0

1/20

2123

/01/

2021

Netherlands France Germany Spain UK Sweden US Japan Belgium

80

GDP growth1 correlates positively with changes inmobility3, even after taking into account lockdownstringency2 and COVID deaths

No clear relationship between GDP growth1 andlockdown stringency2 once changes in mobility3and COVID deaths are taken into account

GDP growth: actual mobility has a stronger impact than thestringency of containment measures

BE Q1BE Q2

BE Q3

-20

-15

-10

-5

0

5

10

15

20

-40 -20 0 20 40 60 80

Resid

ual r

eal G

DP

grow

th (q

oq%

)

Oxford stringency index (qoq change)

BE Q1

BE Q2

BE Q3

-20

-15

-10

-5

0

5

10

15

20

-60 -40 -20 0 20 40 60

Resid

ual r

eal G

DP g

rowt

h (q

oq%

)

Google mobility retail/recreation (qoq change)

2020Q12020Q22020Q3

Sources: OECD, OxCGRT, Google.1 Country sample consists of 45 OECD and major non-OECD countries over 2020Q1-Q3. Each dot represents a country-quarter. Y-axes represent partial residuals from regression of real GDP growth

on lockdown stringency, mobility, COVID deaths and quarter dummies.2 Oxford Stringency index codifies 9 types of containment measures. Index levels take values between 0 (no restrictions) and 100 (hard nationwide lockdown).3 Google mobility report scores for category “retail and recreation”. Level scores indicate percentage deviation from pre-COVID baseline. China is excluded due to lack of data.

81Source: Refinitiv.

Service sector PMIs(diffusion index; 50+ signals expected expansion)

Manufacturing PMIs(diffusion index; 50+ signals expected expansion)

Second wave: lockdowns weigh on sentiment in services

30

35

40

45

50

55

60

6512

/201

9

1/20

20

2/20

20

3/20

20

4/20

20

5/20

20

6/20

20

7/20

20

8/20

20

9/20

20

10/2

020

11/2

020

12/2

020

1/20

21

Euro area US Japan China(Caixin) UK

10

20

30

40

50

60

70

12/2

019

01/2

020

02/2

020

03/2

020

04/2

020

05/2

020

06/2

020

07/2

020

08/2

020

09/2

020

10/2

020

11/2

020

12/2

020

01/2

021

82

Euro area: extra-EA-19 goods export volumes2(% change yoy)

World goods trade volumes1(average of exports and imports, % change yoy)

International trade: World is back to pre-COVID levels, EA lags behind

-30

-25

-20

-15

-10

-5

0

5

10

15

20

1/20

183/

2018

5/20

187/

2018

9/20

1811

/201

81/

2019

3/20

195/

2019

7/20

199/

2019

11/2

019

1/20

203/

2020

5/20

207/

2020

9/20

2011

/202

0World Advanced economiesEmerging economies Euro areaChina

-40-35-30-25-20-15-10-505

101520

1/20

18

3/20

18

5/20

18

7/20

18

9/20

18

11/2

018

1/20

19

3/20

19

5/20

19

7/20

19

9/20

19

11/2

019

1/20

20

3/20

20

5/20

20

7/20

20

9/20

20

11/2

020

Consumer goods (excl. transport eqp.)

Intermediate goods

Capital goodsSources: Netherlands Bureau for Economic Policy Analysis (CPB), Eurostat, Refinitiv.1 Latest available data: November 2020.2 Latest available data: October 2020.

Chinese exportsboosted by demandfor COVID-19-relatedproducts, incl. PPE,medical equipment,work-from-homeelectronics.

-20

-15

-10

-5

0

5

10

Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4

2019 2020

GDP Industry Construction Services

83Source: CEIC.

More balanced between sectors(% change, yoy)

-8

-6

-4

-2

0

2

4

6

8

Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4

2019 2020

Consumption Investment

Net exports GDP growth (in %, YoY)

Equally driven by consumption andinvestment(contribution to growth in percentage points, yoy)

China: Q4 growth back to pre-crisis levels

84Sources: IMF.1 Data cover 73,8 % of world GDP.

Contributions of consumption and investment to world GDP growth1(percentage points, yoy)

Chinese investment pulls global growth out of the through

Strong rebound in private consumption in 2020Q3 suggestsrelease of pent-up demand and adjustments to telework

Investment picked up relatively slowly, except in China

-12

-10

-8

-6

-4

-2

0

2

4

6

Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 Q3

2017 2018 2019 2020

Other EMDEs investmentOther EMDEs private consumptionAEs investmentAEs private consumptionChina investmentChina private consumptionTotal private consumption and investmentWorld GDP growth

85

Selected European countries: Real GDP1(index, 2019Q4 = 100)

Major blocs: Real GDP1(index, 2019Q4 = 100)

Recovery across countries: my way …

7580859095

100105110115

2019

Q4

2020

Q1

2020

Q2

2020

Q3

2020

Q4

2021

Q1

2021

Q2

2021

Q3

2021

Q4

Euro areaUSChinaJapanConsensus forecast (8/1/2021, average of last 8+ revisions)

75

80

85

90

95

100

105

2019

Q4

2020

Q1

2020

Q2

2020

Q3

2020

Q4

2021

Q1

2021

Q2

2021

Q3

2021

Q4

GermanyFranceSpainUKConsensus forecast (8/1/2021, average of last 8+ revisions)

Sources: US Bureau of Economic Analysis (BEA), Consensus Economics, Destatis, Eurostat, Institut national de la statistique et des études économiques (INSEE), Instituto Nacional de Estadística (INE),Japanese Cabinet Office (JP CAO), National Bureau of Statistics of China (NBS), Office for National Statistics (ONS), Refinitiv.

1 Consensus levels implied from forecasted yoy changes.

86

Real GDP forecasts for 20211(%)

Latest IMF forecasts for 2021World Economic Outlook: “Two Shots in the Arm: Stimulus and Vaccines“

Revisions to forecasts for 2021 sinceOctober reflect:

◆ Base effects: somewhat less severecollapse in 2020 than previouslyexpected

◆ Expectations of vaccine-poweredstrengthening of activity later in theyear

◆ Additional policy support in a fewlarge economies (notably US, Japan)

◆ Assumption that new virusoutbreaks remain contained andvaccine rollout proceeds relativelysmoothly

0

2

4

6

8

10

World Euroarea

DE FR IT ES NL BE UK US JP CN

IMF World Economic Outlook Jan 2021 IMF World Economic Outlook Oct 2020

Consensus Jan 2021 (survey mean) Consensus Oct 2020 (survey mean)

Sources: IMF, OECD, Consensus Economics.1 IMF WEO of January 2021 does not include forecasts for BE and NL.

87Source: Consensus Economics. Forecasts up to 25 January 2021.

Euro area: Real GDP growth forecasts, 2021(%)

0

1

2

3

4

5

6

7

13/0

1/20

20

13/0

2/20

20

13/0

3/20

20

13/0

4/20

20

13/0

5/20

20

13/0

6/20

20

13/0

7/20

20

13/0

8/20

20

13/0

9/20

20

13/1

0/20

20

13/1

1/20

20

13/1

2/20

20

13/0

1/20

21

Monthly survey mean Mean on replacement basis Moving average of latest 8+ changes

Belgium: Real GDP growth forecasts, 2021(%)

Consensus forecasts for 2021: not so fast …Latest downgrades for Euro Area growth due to new COVID infections and lockdowns

0

1

2

3

4

5

6

7

13/0

1/20

20

13/0

2/20

20

13/0

3/20

20

13/0

4/20

20

13/0

5/20

20

13/0

6/20

20

13/0

7/20

20

13/0

8/20

20

13/0

9/20

20

13/1

0/20

20

13/1

1/20

20

13/1

2/20

20

13/0

1/20

21

88

Total number of vaccination doses administered per 100 people in the total population1(Situation as of 23 January 2021)

Vaccination kicked off at different speeds

0,8

1,0

1,5

1,5

2,0

2,2

2,5

3,5

6,2

10,1

40,0

0 5 10 15 20 25 30 35 40

Netherlands

China

France

Belgium

Germany

Italy

Spain

Denmark

US

UK

Israel

Source: Our World in Data (OWID).1 Cumulative count of single doses; this may not equal the total number of people vaccinated (which may require receiving multiple doses).

In Belgium, population defined as adult population (those 18 years and older).

89Source: IMF.1 Data are from 13 advanced economies with varying coverage during 1990Q1-2020Q3. Lines are averages across recession types. For the great lockdown, quarter 0 is 2019Q4 for all countries; for

the global financial crisis, quarter 0 is country-specific peak of real GDP during 2007-2008; Other recessions are country-specific episodes of at least two consecutive quarters of negative growthduring 1990-2006 and 2009-2019.

Firms: Zombification or creative destruction?Too early to tell, as temporary measures protect against destruction

Advanced economies: Number of bankruptcies1(index, last pre-recession quarter = 100)

Decline in bankruptcies during great lockdown driven by:

◆ Transfers to firms, credit guarantees and funding-for-lending programmes

◆ Implementation of moratoria on bankruptcy filings insome countries

70

80

90

100

110

120

130

140

-8 -7 -6 -5 -4 -3 -2 -1 0 1 2 3 4 5 6 7 8Recession quarter

Great Lockdown, 2020Global financial crisis, 2007–2008Other recessions

90

NBB online surveysin cooperation with the

Microsoft Innovation Center

91

NBB Survey on impact on households’ income

7-24 May

Press releasePerscommuniquéCommuniqué de presse

https://www.nbb.be/en/articles/coronavirus-crisis-having-heavy-impact-some-households-income-bringing-even-bigger-losseshttps://www.nbb.be/nl/artikels/de-coronacrisis-heeft-een-aanzienlijke-negatieve-impact-op-de-inkomens-van-bepaaldehttps://www.nbb.be/fr/articles/la-crise-du-coronavirus-un-impact-negatif-imp