2156
Views
637
Downloads |
The impact of the COVID-19 crisis on income distribution under different protection schemes: the case of Spain
Gonzalo Gómez Bengoechea* 
Article | Year: 2021 | Pages: 517 - 541 | Volume: 45 | Issue: 4 Received: June 14, 2021 | Accepted: August 21, 2021 | Published online: December 6, 2021
|
FULL ARTICLE
FIGURES & DATA
REFERENCES
CROSSMARK POLICY
METRICS
LICENCING
PDF
Note: OECD countries. 2019 or latest year with available data. Source: OECD statistics.
|
Economic
sector
|
Aggregate variation in total
compensations March-April 2020
|
|
Agriculture
|
6.46
|
|
Other professional
activities
|
-9.60
|
|
Industrial
production
|
-11.45
|
|
Total for all sectors
|
-14.35
|
|
Arts
& education
|
-14.37
|
|
Financial
services
|
-14.90
|
|
Retail
|
-14.99
|
|
Manufacturing
|
-20.20
|
|
Construction
|
-20.20
|
|
Real-estate
|
-22.62
|
|
Hospitality
|
-75.80
|
Source: Authors’ estimations based on ECV data.
|
% of at-risk income lost
|
|
|
10
|
20
|
30
|
40
|
50
|
60
|
70
|
80
|
90
|
100
|
|
% of at-risk households
losing income
|
10
|
0.2
|
0.3
|
0.5
|
0.6
|
0.8
|
0.9
|
1.1
|
1.2
|
1.4
|
1.5
|
|
20
|
0.3
|
0.6
|
0.9
|
1.2
|
1.5
|
1.8
|
2.1
|
2.4
|
2.7
|
3.0
|
|
30
|
0.5
|
0.9
|
1.4
|
1.9
|
2.4
|
2.8
|
3.3
|
3.8
|
4.2
|
4.7
|
|
40
|
0.6
|
1.2
|
1.9
|
2.5
|
3.1
|
3.7
|
4.3
|
4.9
|
5.6
|
6.2
|
|
50
|
0.8
|
1.5
|
2.3
|
3.1
|
3.9
|
4.6
|
5.4
|
6.2
|
6.9
|
7.7
|
|
60
|
0.9
|
1.8
|
2.8
|
3.7
|
4.6
|
5.5
|
6.4
|
7.4
|
8.3
|
9.2
|
|
70
|
1.1
|
2.1
|
3.2
|
4.3
|
5.3
|
6.4
|
7.5
|
8.5
|
9.6
|
10.7
|
|
80
|
1.2
|
2.4
|
3.6
|
4.8
|
6.0
|
7.2
|
8.4
|
9.6
|
10.8
|
12.0
|
|
90
|
1.3
|
2.7
|
4.0
|
5.4
|
6.7
|
8.1
|
9.4
|
10.7
|
12.1
|
13.4
|
|
100
|
1.5
|
3.0
|
4.4
|
5.9
|
7.4
|
8.9
|
10.4
|
11.8
|
13.3
|
14.8
|
|
|
Income contraction
scenarios
|
|
Low-income
protection schemes
|
Concentrated
losses under NLIB
|
Dispersed losses under NLIB
|
|
Concentrated
losses under RMI
|
Dispersed losses under RMI
|
|
Concentrated
losses under IMV
|
Dispersed losses under IMV
|
|
Concentrated losses (90-80)
|
|
NUBI
|
Pre-COVID
|
Post-COVID
|
Change
|
New poor
|
|
1.9 $ /
day
|
0.75
|
0.89
|
0.14
|
67,682
|
|
3.2 $ /
day
|
0.80
|
1.01
|
0.21
|
101,286
|
|
5.5 $ /
day
|
0.86
|
1.19
|
0.34
|
159,502
|
|
National
poverty line
|
6.70
|
8.06
|
1.36
|
643,688
|
|
RMI
|
Pre-COVID
|
Post-COVID
|
Change
|
New poor
|
|
1.9 $ /
day
|
0.43
|
0.56
|
0.13
|
61,529
|
|
3.2 $ /
day
|
0.46
|
0.65
|
0.19
|
88,507
|
|
5.5 $ /
day
|
0.48
|
0.80
|
0.32
|
152,876
|
|
National
poverty line
|
6.49
|
8.01
|
1.52
|
719,416
|
|
RMV
|
Pre-COVID
|
Post-COVID
|
Change
|
New poor
|
|
1.9 $ /
day
|
0.45
|
0.53
|
0.08
|
37,391
|
|
3.2 $ /
day
|
0.49
|
0.58
|
0.09
|
42,124
|
|
5.5 $ /
day
|
0.51
|
0.67
|
0.16
|
74,781
|
|
National
poverty line
|
6.18
|
7.69
|
1.51
|
716,103
|
|
Dispersed losses (80-90)
|
|
NUBI
|
Pre-COVID
|
Post-COVID
|
Change
|
New poor
|
|
1.9 $ /
day
|
0.75
|
0.85
|
0.10
|
48,750
|
|
3.2 $ /
day
|
0.80
|
0.93
|
0.13
|
59,162
|
|
5.5 $ /
day
|
0.86
|
1.02
|
0.16
|
74,781
|
|
National
poverty line
|
6.70
|
8.13
|
1.43
|
678,712
|
|
RMI
|
Pre-COVID
|
Post-COVID
|
Change
|
New poor
|
|
1.9 $ /
day
|
0.43
|
0.53
|
0.11
|
50,643
|
|
3.2 $ /
day
|
0.46
|
0.58
|
0.12
|
58,689
|
|
5.5 $ /
day
|
0.48
|
0.64
|
0.16
|
77,621
|
|
National
poverty line
|
6.49
|
8.08
|
1.59
|
753,493
|
|
RMV
|
Pre-COVID
|
Post-COVID
|
Change
|
New poor
|
|
1.9 $ /
day
|
0.45
|
0.50
|
0.05
|
22,245
|
|
3.2 $ /
day
|
0.49
|
0.55
|
0.06
|
29,345
|
|
5.5 $ /
day
|
0.51
|
0.58
|
0.08
|
35,497
|
|
National
poverty line
|
6.18
|
7.76
|
1.58
|
747,814
|
|
Concentrated losses
|
|
|
Ex ante
|
Ex post
|
% change
|
|
NUBI
|
0.498
|
0.567
|
13.9
|
|
RMI
|
0.450
|
0.510
|
13.3
|
|
RMV
|
0.434
|
0.494
|
13.9
|
|
Dispersed losses
|
|
NUBI
|
0.498
|
0.550
|
10.5
|
|
RMI
|
0.450
|
0.493
|
9.6
|
|
RMV
|
0.434
|
0.477
|
10.0
|
Source: Author’s estimations based on ECV data.
|
|
Concentrated losses
|
Dispersed losses
|
|
|
From high to middle
|
From middle to poor
|
From high to middle
|
From middle to poor
|
|
NUBI
|
5.7
|
2.0
|
3.7
|
1.0
|
|
RMI
|
5.9
|
1.2
|
3.6
|
0.6
|
|
IMV
|
5.9
|
0.8
|
3.3
|
0.4
|
|
Country
|
Gini Index
|
Poverty rates
|
Social spending
(% of GDP)
|
|
Austria
|
0.28
|
9.4
|
26.9
|
|
Belgium
|
0.26
|
8.2
|
28.9
|
|
Canada
|
0.30
|
11.8
|
18.0
|
|
Chile
|
0.46
|
16.5
|
11.4
|
|
Chzech
Republic
|
0.25
|
6.1
|
19.2
|
|
Costa
Rica
|
0.50
|
19.9
|
12.2
|
|
Denmark
|
0.26
|
6.1
|
28.3
|
|
Deutschland
|
0.29
|
10.4
|
25.9
|
|
Estonia
|
0.31
|
16.3
|
17.7
|
|
Finland
|
0.27
|
6.5
|
29.1
|
|
France
|
0.30
|
8.5
|
31.0
|
|
Great
Britain
|
0.37
|
11.7
|
20.6
|
|
Greece
|
0.31
|
12.1
|
24.0
|
|
Hungary
|
0.29
|
8.0
|
18.1
|
|
Ireland
|
0.29
|
9.0
|
13.4
|
|
Israel
|
0.25
|
16.9
|
16.3
|
|
Italy
|
0.33
|
13.9
|
28.2
|
|
Latvia
|
0.34
|
17.5
|
16.4
|
|
Lithuania
|
0.36
|
15.5
|
16.7
|
|
Luxembourg
|
0.32
|
11.4
|
21.6
|
|
Mexico
|
0.42
|
16.6
|
7.5
|
|
Netherlands
|
0.29
|
8.3
|
16.1
|
|
Norway
|
0.26
|
8.4
|
25.3
|
|
Poland
|
0.28
|
9.8
|
21.3
|
|
Portugal
|
0.32
|
10.4
|
22.6
|
|
Slovakia
|
0.24
|
7.7
|
17.7
|
|
Slovenia
|
0.25
|
7.5
|
21.1
|
|
South
Korea
|
0.35
|
16.7
|
12.2
|
|
Spain
|
0.33
|
14.2
|
24.7
|
|
Sweden
|
0.28
|
8.9
|
25.5
|
|
Switzerland
|
0.30
|
9.2
|
16.7
|
|
United States
|
0.39
|
17.8
|
18.7
|
Note: OECD Countries, 2019 or latest year with available data. Source: Author’s estimations based on OECD statistics.
|
Protection
scheme and region
|
Min. benefit amount
|
Max. benefit amount
|
|
RMI Andalucía
|
5,287.44
|
4,541.88
|
|
RMI Aragón
|
5,892.00
|
5,892.00
|
|
RMI Asturias
|
5,315.52
|
3,455.04
|
|
RMI Baleares
|
5,178.36
|
4,140.60
|
|
RMI Canarias
|
5,745.24
|
2,267.76
|
|
RMI Cantabria
|
5,163.24
|
2,904.36
|
|
RMI Castilla- La
Mancha
|
5,357.40
|
4,079.76
|
|
RMI Castilla y León
|
5,168.40
|
3,221.88
|
|
RMI Cataluña
|
7,248.00
|
6,216.00
|
|
RMI Ceuta
|
3,600.00
|
1,440.00
|
|
RMI Extremadura
|
5,163.24
|
3,549.73
|
|
RMI Galicia
|
5,084.16
|
4,067.28
|
|
RMI La Rioja
|
5,163.24
|
2,904.36
|
|
RMI Madrid
|
4,800.00
|
5,722.20
|
|
RMI Melilla
|
5,503.68
|
3,669.12
|
|
RMI Murcia
|
5,163.24
|
4,517.88
|
|
RMI Navarra
|
7,329.60
|
7,329.60
|
|
RMI Valencia
|
3,090.84
|
6,623.04
|
|
RMI País Vasco
|
7,733.88
|
4,130.64
|
|
IMV National
|
5,544.00
|
6,636.00
|
|
Economic sector
|
Decile 1
|
Decile 2
|
Decile 3
|
Decile 4
|
Decile 5
|
Decile 6
|
Decile 7
|
Decile 8
|
Decile 9
|
Decile 10
|
|
Agriculture
|
13.2
|
13.4
|
16.0
|
11.2
|
6.3
|
3.8
|
3.2
|
2.8
|
1.8
|
0.7
|
|
Arts
& education
|
7.9
|
9.1
|
5.5
|
5.3
|
5.3
|
6.8
|
8.3
|
10.8
|
11.7
|
14.1
|
|
Construction
|
5.3
|
7.7
|
7.8
|
7.8
|
8.8
|
7.9
|
6.8
|
5.2
|
6.3
|
4.2
|
|
Financial
services
|
2.6
|
0.5
|
1.2
|
0.7
|
1.1
|
1.2
|
1.3
|
2.7
|
3.1
|
5.9
|
|
Hospitality
|
13.2
|
7.2
|
11.9
|
9.5
|
10.6
|
8.1
|
6.8
|
6.3
|
5.2
|
2.8
|
|
Industrial
production
|
5.3
|
4.3
|
4.6
|
6.4
|
6.8
|
7.8
|
6.9
|
7.6
|
7.0
|
6.2
|
|
Manufacturing
|
0.0
|
9.6
|
8.2
|
10.5
|
12.8
|
15.3
|
12.8
|
15.7
|
16.8
|
15.0
|
|
Other
professional activities
|
28.9
|
28.2
|
27.1
|
27.5
|
26.8
|
29.6
|
31.4
|
29.6
|
29.9
|
33.7
|
|
Real-estate
|
0.0
|
0.0
|
0.2
|
0.6
|
1.0
|
0.7
|
0.5
|
0.7
|
0.6
|
1.0
|
|
Retail
|
21.1
|
17.7
|
15.1
|
16.6
|
16.7
|
14.8
|
17.8
|
13.2
|
12.8
|
10.3
|
Source: Author’s estimations based on ECV data.
Figure 1Social spending as a percentage of GDP (vertical axis) and Gini Index (horizontal axis) DISPLAY Figure
Table 1Aggregate variation in total compensations March-April 2020 by economic sector (in percent) DISPLAY Table
Figure 2Income composition under different protection schemes DISPLAY Figure
Table 2Scenarios for income losses as a percentsge of total household income DISPLAY Table
Table 3Low-income protection schemes and income contraction scenarios DISPLAY Table
Table 4Concentrated losses scenarios, incidence on different poverty lines (percentage of population living under each line) DISPLAY Table
Table 5Dispersed losses scenarios, incidence on different poverty lines (percentage of population living under each line) DISPLAY Table
Table 6Gini Index for concentrated and dispersed losses under different protection schemes DISPLAY Table
Figure 3Incidence curves for at-risk incomes DISPLAY Figure
Table 7Income mobility by income group (in percent) DISPLAY Table
Table A1Gini Index, poverty rates and social spending DISPLAY Table
Table A2Minimum and maximum benefit amounts: RMI regional and IMV national low income protection schemes (in €) DISPLAY Table
Table A3Percentage of individuals in each economic sector per decile of ex-ante gross Income per capita DISPLAY Table
Figure A1Gini Index for 10% and 100% of households losing from 0% to 100% of at-risk income DISPLAY Figure
* The author would like to thank two anonymous referees for their useful comments and suggestions and the generous contributions by Lucía Blasco Guzmán, Siyu Quan and Valentina Vidal to this article. The previous version was published at: http://repec.tulane.edu/RePEc/ceq/ceq102.pdf.
1 I have excluded Chile, Costa Rica, and Mexico for representation purposes. Their figures, as well as those of the other countries included in Figure 1, are shown in Table 8 at the Appendix section
2 Economic Sectors follow the classification of the Spanish Tax Office, while workers are categorized according to ILO rules. As a consequence, some regrouping is necessary to merge information. Complementary Professional Activities include logistics, telecommunications and other supporting services. Industrial Production includes all industries but manufacturing, i.e., extractive industries, energy production and waste management.
|
|
December, 2021
IV/2021 |
