Figures and tables in In-work Benefits in Belgium: Effects on Labour Supply and Welfare

Abstract

Belgium has implemented, following the example of other countries, in-work benefit policies since the early 2000’s, with the objective of increasing employment rates and fighting poverty. Belgian in-work benefits differ from most other in-work benefits as eligibility requires low hourly earnings. We study the effects extensions of those benefits would have both on labour supply and welfare, using a random-utility - random-opportunity model estimated on cross-sectional SILC datasets. Results show that further increasing the benefits would slightly increase labour supply and welfare of low-to-middle income deciles, but at very high net cost per job created. We compare our results with existing research and explain some mechanisms that possibly led to an underestimation of negative intensive margin labour supply responses in previous simulations.

This article contains 17 figures and 14 tables.

Figures

**Figure 1.** Unemployment rate by level of education (Source: OECD)

**Figure 2.** Labour supply distribution of men (left) and women (right) in the sample

**Figure 3.** Estimated indifference curves

**Figure 4.** Estimated job offer intensity (2016)

**Figure 5.** Effect of covariates on wage offers

**Figure 6.** Estimated evolution of hourly wages

**Figure 7.** Estimated hours offers distribution

**Figure 8.** Level of WB in function of gross wage (full-time worker) and gross wage distribution

**Figure 9.** Budget set of single working at min. wage - base and reform 1

**Figure 10.** Decomposition of labour supply changes

**Figure 11.** Welfare changes following reform 1

**Figure A1.** Welfare changes following reform 2

**Figure A2.** Welfare changes following reform 3

**Figure A3.** Simulated and observed hours distributions

**Figure A4.** Simulated and observed wage distributions

**Figure A5.** Estimated disposable income distribution

**Figure A6.** Estimated disposable income distribution

Tables

Table 1. Policy parameters (2016): Work-Bonus and Fiscal Work-Bonus

Parameter	Unit	Value
A	EUR/month	193.79
θ ₁	EUR/month	1,577.89
θ₂	EUR/month	2,461.27
ρ ₁	%	21.94
ρ ₂	%	28.03

Table 2. Descriptive statistics - households included in the estimation sample

	Single		Couple
	Male	Female	Male	Female
Number of observations	4057	4585	8344
Av. working time - Workers (h/week)	39.6	34.9	40.7	32.9
Average hourly gross wage (EUR/h)	20.3	19.9	22.2	19.7
Participation (%)	77.3	74.7	96.1	92.6
Highest level of education (%) - Workers
- Primary or no education	6.1	5.2	4.4	3.8
- Lower secondary education	13.3	10.7	11.0	8.0
- Upper secondary education	37.2	31.4	36.0	30.2
- High education	43.5	52.8	48.6	57.9
Highest level of education (%) - Non-workers
- Primary or no education	24.1	25.3	22.5	14.8
- Lower secondary education	28.4	23.1	22.2	24.7
- Upper secondary education	27.8	33.2	36.4	35.6
- High education	19.7	18.5	18.8	25.0
Household composition
Average household size	1.4	1.8	3.3
- of which children	0.1	0.6	1.3

Table 3. Descriptive statistics - overtime workers in sub-sample

	Work regime		Comparison
	All	Overtime
	(>0h/w)	(>40h/w)
Average age	40.4	40.4	+0
Average working time (h/week)	37.1	49.5	+12.4
Average years of education	13.3	14.4	+1.1
Average gross hourly wage (EUR ₂₀₁₆)	20.7	21.5	+0.8
Average gross earnings (EUR ₂₀₁₆)	3310.5	4569.7	+1259.2
Percentage of males	51.9	72.6	+20.7
Type of ISCO occupation (%)
- 0: Armed forces	0.7	0.5	-0.2
- 1: Senior officials and managers	6.5	18.2	+11.7
- 2: Professionals	23.5	32.2	+8.7
- 3: Technicians	16.0	15.0	-1.0
- 4: Clerical support workers	19.3	11.9	-7.4
- 5: Services and sales workers	9.9	6.7	-3.2
- 6: Skilled agricultural	0.4	0.3	-0.1
- 7: Craft and trade workers	8.5	6.4	-2.1
- 8: Plant and machine operators	6.0	5.9	-0.1
- 9: Elementary occupations	9.2	2.8	-6.4

Table 4. Model specification - covariates

	Preferences		Opportunities
		intensity job offers	hours	wages
	<disp-formula> $X_{l}$ </disp-formula>	<disp-formula> $X_{o}$ </disp-formula>	<disp-formula> $X_{h}$ </disp-formula>	<disp-formula> $X_{w}$ </disp-formula>
Regional dummies	yes	yes	no	no
Education dummies	yes	yes	no	yes
Age	yes	no	no	no
Group-specific unemp.	no	yes	no	no
Number of children	yes	no	no	no
Gender	yes	yes	yes	yes
Experience	no	no	no	yes
Year	no	yes*	no	yes

Included implicitly as group-specific unemployment rates are year-specific.

Table 5. Marginal utilities

% Observations	Single Male	Single Female	Couples
<disp-formula> $U_{d}^{'}$ </disp-formula>	100	100	100
<disp-formula> $U_{t}^{'}$ </disp-formula>	100	100	Male: 99.89Female: 99.86

Table 6. Elasticities and participation changes (10

%

wage increase)

	Increase of male wages			Increase of female wages
	Single	Couple		Single	Couple
	Male	Male	Female	Female	Male	Female
Total elasticity	0.270	0.117	-0.072	0.210	-0.067	0.163
Intensive margin	0.049	0.068	-0.090	0.042	-0.087	0.106
Participation (entering, % of total)	1.791	0.506	0.193	1.388	0.214	0.548
Participation (leaving, % of total)	0.025	0.000	0.531	0.000	0.535	0.000

Table 7. Effects of the reforms on labour supply

Overview LS effects	Param.	Base	Ref1	Ref2	Ref3
	<disp-formula> $A$ </disp-formula>	193.79	257.81	222.05	193.79
	<disp-formula> $θ_{1}$ </disp-formula>	1577.89	1577.89	1577.89	1577.89
	<disp-formula> $θ_{2}$ </disp-formula>	2461.27	2461.27	2590.07	2721.83
	<disp-formula> $ρ 1$ </disp-formula>	21.94	29.18	21.94	16.94
	<disp-formula> $ρ 1$ </disp-formula>	28.03	28.03	28.03	28.03
ΔLabour supply (FTE)			+669 (+0.032%)	+141 (+0.007%)	-362 (-0.017%)
- Ext. margin (FTE)			+1609	+895	+530
- Int. margin (FTE)			-939	-754	-892
ΔParticipation			+2024 (+0.093%)	+1200 (+0.055%)	+688 (+0.032%)
- people starting to work			2831	1697	964
- people stopping to work			807	497	276
ΔTotal gross labour income (M EUR)			-190.2 (-0.217%)	-166.3 (-0.190%)	-105.3 (-0.120%)
- average gross wage change (EUR/h)			-0.053	-0.041	-0.022

Table 8. Effects of the reforms on poverty and inequality

Poverty and Inequality	Base	Ref1	Ref2	Ref3
Gini	21.25	21.18	21.19	21.20
Poverty rate	10.37	10.20	10.22	10.26

Table 9. Effects of the reforms on budget balance (Million EUR)

Budget Balance	Ref1	Ref2	Ref3
+Δ Social Security contrib. (static)	-83.4	-82.4	-82.9
+Δ Personal Income Tax (static)	-234.9	-233.2	-232.1
–Δ Benefits (static)	-16.7	-15.9	-15.2
=Δ Budget balance (static)*	-301.5	-299.7	-299.7
Additional impact following LS changes
+Δ Social Security contrib.	-176.1	-168.8	-160.4
+Δ Personal Income Tax	+40.9	+53.0	+82.3
–Δ Benefits	-23.8	-17.8	-12.7
=Δ Budget balance (total)*	-413.0	-397.7	-365.2

A negative balance corresponds to a deficit for the government.

Table 10. Net costs to increase labour supply (Thousand EUR)

Net costs	Ref1	Ref2	Ref3
Cost / additional FTE	368.5	1660.1	-
Cost / additional participant	121.1	195.1	560.7

Preferences	Estimate	Standard Error	t-value
Single male
Leisure
Constant	8.380	2.074	4.041
Log(age)	-4.654	1.145	-4.065
Log(age)²	0.665	0.158	4.208
Children 4-6	-0.117	0.073	-1.611
Children 7-9	0.002	0.072	0.034
Wallonia	0.125	0.035	3.578
Brussels	0.058	0.030	1.901
Low education	0.072	0.040	1.799
High education	-0.044	0.026	-1.670
Exponent	-9.217	0.414	-22.262
Income
Constant	1.526	0.057	26.696
Exponent	0.721	0.036	20.250
Single female
Leisure
Constant	24.608	4.348	5.660
Log(age)	-13.548	2.392	-5.665
Log(age)²	1.913	0.331	5.784
Children 0-3	0.297	0.104	2.864
Children 4-6	0.155	0.078	1.982
Children 7-9	0.116	0.064	1.824
Wallonia	0.145	0.047	3.093
Brussels	-0.025	0.040	-0.613
Low education	0.321	0.088	3.646
High education	-0.332	0.052	-6.400
Exponent	-9.005	0.351	-25.662
Income
Constant	1.604	0.062	25.748
Exponent	0.681	0.037	18.356

Preferences	Estimate	Standard Error	t-value
Couples
Leisure
Constant leisureM	5.637	0.110	51.210
Log(age)	-3.117	0.061	-51.380
Log(age)²	0.443	0.011	41.785
Children 0-3	0.012	0.009	1.287
Children 4-6	0.003	0.010	0.326
Children 7-9	0.003	0.009	0.343
Wallonia	0.042	0.011	3.738
Brussels	0.036	0.015	2.347
Low education	0.053	0.018	2.885
High education	-0.003	0.010	-0.293
Constant leisureF	13.996	5.220	2.681
Log(age)	-7.480	2.900	-2.579
Log(age)²	1.100	0.403	2.730
Children 0-3	0.137	0.049	2.821
Children 4-6	0.151	0.052	2.882
Children 7-9	0.031	0.046	0.676
Wallonia	0.123	0.053	2.303
Brussels	-0.159	0.064	-2.508
Low education	0.091	0.103	0.888
High education	-0.402	0.064	-6.275
Exponent leisureM	-10.872	0.243	-44.764
Exponent leisureF	-8.371	0.264	-31.751
Income
Constant	3.016	0.122	24.687
Exponent	0.561	0.028	20.351
Cross-effect
Cross-effect leisure	0.032	0.005	6.541

Opportunities	Estimate	Standard Error	t-value
Male
Intensity
Working	-3.899	0.090	-43.151
Group specific unemp.	0.011	0.004	2.898
Wallonia	-0.626	0.088	-7.133
Brussels	-1.084	0.102	-10.655
Low education	-0.894	0.094	-9.477
High education	0.484	0.102	4.758
Offered time regimes
Part-time dummy 1	0.618	0.092	6.725
Part-time dummy 2	0.909	0.082	11.106
Full-time dummy	2.543	0.031	80.733
Offered wages
Constant	2.407	0.017	143.643
Low education	-0.121	0.011	-11.476
High education	0.247	0.007	33.057
Experience	2.290	0.140	16.404
Experience²	-3.063	0.307	-9.969
Standard dev.	0.295	0.001	315.096
Female
Intensity
Working	-3.237	0.077	-42.108
Group specific unemp.	-0.021	0.003	-6.481
Wallonia	-0.540	0.077	-7.050
Brussels	-0.879	0.094	-9.383
Low education	-0.677	0.090	-7.522
High education	0.565	0.089	6.352
Offered time regimes
Part-time dummy 1	1.496	0.050	30.180
Part-time dummy 2	1.731	0.055	31.664
Full-time dummy	2.055	0.033	61.666
Offered wages
Constant	2.303	0.016	141.385
Low education	-0.079	0.012	-6.793
High education	0.273	0.008	33.886
Experience	2.650	0.131	20.200
Experience^2	-3.950	0.295	-13.400
Standard dev.	0.304	0.001	395.650

Opportunities	Estimate	Standard Error	t-value
Wage eq. year dummies
2006 dummy	-0.212	0.010	-21.924
2007 dummy	-0.178	0.009	-19.012
2008 dummy	-0.179	0.009	-19.061
2010 dummy	-0.133	0.009	-14.050
2012 dummy	-0.078	0.010	-7.982
2015 dummy	-0.025	0.010	-2.580
2016 dummy	0.009	0.010	0.908