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French do it better. The distributive effect of introducing French family fiscal policies in Italy

  1. Paolo Brunori  Is a corresponding author
  2. Maria Luisa Maitino  Is a corresponding author
  3. Letizia Ravagli  Is a corresponding author
  4. Nicola Sciclone  Is a corresponding author
  1. Università degli Studi di Firenze, Italy
  2. Istituto Regionale Programmazione Economica della Toscana, Italy
Research article
Cite this article as: P. Brunori, M. Luisa Maitino, L. Ravagli, N. Sciclone; 2020; French do it better. The distributive effect of introducing French family fiscal policies in Italy; International Journal of Microsimulation; 13(1); 2-18. doi: 10.34196/ijm.00210
6 figures and 9 tables

Figures

Distributive effects by deciles of equivalent gross household income (a)Tax difference (euro) (b) % change of income tax incidence.

Source: MicroReg based on EUSILC, 2016 (2016). 95% confidence intervals obtained with 200 bootstrap resamplings.

Distributive effects by number of children and deciles of equivalent gross household income (a) Tax difference by number of children (euro) (b) % change of income tax incidence.

Source: MicroReg based on EUSILC, 2016 (2016). Confidence intervals obtained with 200 bootstrap resamplings.

Distributive effects by number of children and deciles of equivalent gross household income (a) Family transfers difference by number of children (euro) (b) % change of family transfers.

Source: MicroReg based on EUSILC, 2016 (2016). Confidence intervals obtained with 200 bootstrap resamplings.

Figure A1–1
Figure B.1 Distributive effects by deciles of equivalent gross household income (a)Tax difference (euro) (b) % change of income tax incidence.

Source: MicroReg based on EUSILC, 2016 (2016). 95% confidence intervals obtained with 200 bootstrap resamplings.

Figure A1–2
Figure B.2 Distributive effects by number of children and deciles of equivalent gross household income (a) Tax difference by number of children (euro) (b) % change of income tax incidence.

Source: MicroReg based on EUSILC, 2016 (2016). Confidence intervals obtained with 200 bootstrap resamplings.

Figure A1–3
Figure B.3 Distributive effects by number of children and deciles of equivalent gross household income (a) Family transfers difference by number of children (euro) (b) % change of family transfers.

Source: MicroReg based on EUSILC, 2016 (2016). Confidence intervals obtained with 200 bootstrap resamplings.

Tables

Table 1
The French “family quotient” (QF)
Household type and children Part
Married or cohabiting couples 2
Single 1
Single parent with at least one dependent child 1.5
Widow/er/s with at least one dependent child 2
First child 0.5
Second child 0.5
Every child after the second 1
Table 2
Income tax features in Italy and France
Italy France
Taxation unit Individual “Fiscal household”
Gross income Total individual income Total household income
Deductions Deductions for pension contributions, first home cadastral income and others Deduction for income source
Net taxable income Total individual income net of deductions (y) Total household income net of deductions (y) divided by number of “parts” (QF)
Legal rates 23% up to 15,000 euros
27% from 15,000–28,000 euros
38% from 28,000–55,000 euros
41% from 55,000–75,000 euros
43% over 75,000 euros
0% from 0 to 9,700 euros
14% from 9,701–26,791 euros
30% from 26,792–71,826 euros
41% from 71,827–152,108 euros
45% over 152,108 euros
Tax credits Tax credits for income source
Tax credits for household dependents (spouse, children and other household members)
Other minor tax credits
Tax relief (Décote) and other minor tax credits
Net tax y×rate-taxcredits Max{yQF× rate × QF;IqMAX}tax credits
Table 3
Average tax rate paid on participation for non-working Italian women by household equivalent income deciles and number of children
Decile/n° children 0 1 2 3 or more
1 −2.24% −3.02% −4.73% −6.1%
2 2.63% 2.39% 0.90% −1.9%
3 5.91% 9.72% 6.65% 3.4%
4 7.31% 9.31% 9.99% 8.8%
5 9.27% 8.92% 11.98% 7.2%
6 6.72% 11.97% 9.57% 8.4%
7 8.11% 10.76% 6.67% 11.0%
8 8.80% 14.82% 13.02% 17.3%
9 9.16% 10.28% 16.90% 17.2%
10 11.25% 13.24% 18.19% 13.5%
  1. Source: MicroReg based on EUSILC, 2016 (2016).

Table 4
Average tax rate paid on participation for non-working Italian women by household equivalent income deciles
Decile Predicted income Participation tax rate today Participation tax rate after reform Difference Share facing higher tax rate after reform
1 21,766.40 17.25% 14.07% −3.18% 5.34%
2 21,219.29 17.21% 18.75% 1.54% 58.13%
3 21,002.73 18.61% 24.89% 6.28% 86.83%
4 22,074.95 17.73% 26.05% 8.32% 86.59%
5 22,650.10 17.30% 26.91% 9.61% 87.50%
6 29,427.52 20.02% 27.94% 7.92% 87.43%
7 27,369.19 17.98% 26.28% 8.30% 86.06%
8 21,432.34 15.09% 25.39% 10.30% 82.34%
9 26,948.72 17.74% 27.62% 9.88% 82.82%
10 28,348.04 17.78% 29.93% 12.15% 81.66%
  1. Source: MicroReg based on EUSILC, 2016 (2016).

Table 5
Percentage distribution of subsidies by deciles of equivalent gross household income
Decile Post reform Pre reform
AF PAJE PN ARS ASF CF Total BB PN AF AF3 Total
1 18% 17% 13% 30% 24% 31% 19% 17% 9% 11% 45% 15%
2 21% 19% 21% 32% 15% 40% 23% 28% 15% 22% 46% 24%
3 12% 14% 10% 23% 11% 13% 14% 9% 7% 17% 9% 15%
4 10% 16% 18% 11% 13% 7% 11% 12% 13% 13% 0% 12%
5 9% 13% 10% 2% 8% 5% 9% 7% 7% 9% 0% 8%
6 9% 13% 16% 1% 9% 5% 9% 10% 11% 8% 0% 8%
7 9% 6% 10% 0% 6% 0% 7% 8% 9% 9% 0% 8%
8 6% 1% 1% 0% 4% 0% 4% 8% 13% 6% 0% 6%
9 4% 0% 0% 0% 7% 0% 2% 1% 8% 4% 0% 3%
10 2% 0% 1% 0% 4% 0% 1% 0% 6% 2% 0% 2%
Total 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100%
  1. Source: MicroReg based on EUSILC, 2016 (2016).

Table 6
Indices of inequality of the equivalent gross household income
Pre reform After reform
point low high point low high
Gross income (Gini) 0.3977 0.3919 0.4032
Gross income – tax (Gini) 0.3515 0.3455 0.3567 0.3493 0.3439 0.3549
Tax-Kakwani 0.1883 0.1848 0.1908 0.1899 0.1868 0.1935
Transfer-Kakwani −0.703 −0.7309 −0.6753 −0.7547 −0.7767 −0.7331
Disposable income 0.3467 0.3409 0.3519 0.3449 0.3396 0.3507
  1. Source: MicroReg based on EUSILC, 2016 (2016). Confidence intervals obtained with 200 bootstrap resamplings. Note that 95% confidence bounds do no overlap for Gross income – tax (Gini) and Transfer-Kakwani but do overlap for Tax-Kakwani and Disposable income.

Table A.1
Amount and recipients of Italian subsidies by benefit and number of children
1 2 3+ Total
Baby bonus Average amount (euro) 1,117 1,397 1,422 1,281
Recipients (thousand) 165 168 54 388
Amount (billion euro) 185 235 78 498
Birth bonus Average amount (euro) 800 834 825 817
Recipients (thousand) 225 203 57 485
Amount (billion euro) 180 169 47 396
Family allowance Average amount (euro) 800 1,369 2,614 1,248
Recipients (thousand) 1,748 1,706 423 3,878
Amount (billion euro) 1,398 2,337 1,106 4,841
Municipal family allowances for households with three children Average amount (euro) 1,696 1,696
Recipients (thousand) 316 316
Amount (billion euro) 536 536
Total Average amount (euro) 926 1,523 3,274 1,478
Recipients (thousand) 1,903 1,799 539 4,242
Amount (billion euro) 1,764 2,741 1,767 6,271
  1. Source: MicroReg based on EUSILC, 2016 (2016)

Table A.2
Amount and recipients of French subsidies by benefit and number of children
1 2 3+ Total
Allocation Familiale Average amount (euro) 1,938 4,491 2,392
Recipients (thousand) 3,210 694 3,904
Amount (billion euro) 6,222 3,119 9,341
Prestation d´Accueil du Jeune Enfant Average amount (euro) 1,994 2,075 2,181 2,052
Recipients (thousand) 560 554 160 1,273
Amount (billion euro) 1,230 1,213 392 2,836
Prime de naissance Average amount (euro) 928 966 962 951
Recipients (thousand) 126 152 49 327
Amount (billion euro) 121 153 52 325
Allocation de rentrée scolaire Average amount (euro) 377 579 915 575
Recipients (thousand) 759 1,242 427 2,428
Amount (billion euro) 286 719 390 1,395
Allocation de soutien familial Average amount (euro) 110 219 323 157
Recipients (thousand) 766 403 64 1,233
Amount (billion euro) 84 88 21 193
Complément familial Average amount (euro) 2,616 2,616
Recipients (thousand) 294 294
Amount (billion euro) 890 890
Total Average amount (euro) 943 2,586 6,757 2,605
Recipients (thousand) 1,700 3,220 695 5,614
Amount (billion euro) 1,722 8,395 4,863 14,980
  1. Source: MicroReg based on EUSILC, 2016 (2016)

Table A.3
Heckman selection model for women’s participation wage
Variable Coeff P-value St. sig.
log labor income
age 0.0628 0.0106 ***
age2 −0.0005 0.0001 ***
north 0.0832 0.053
center −0.0336 0.0489
comp. edu. −0.4583 0.0731 ***
secondary edu −0.2166 0.03299 ***
constatnt 8.2617 0.2634 ***
working
age 0.1312 0.009 ***
age2 −0.0015 0.0001 ***
north 0.6996 0.0337 ***
center 0.5289 0.0389 ***
comp. edu. −1.1664 0.0434 ***
secondary edu −0.4476 0.0417 ***
# children −0.1908 0.0155 ***
constatnt −1.7206 0.1881 ***
Mills
lambda −0.4535 0.1173 ***
rho 0.5032
sigma 0.9011
  1. Note: Dependent variables are the log of the yearly labour income and the probability to be working, number of observations 9,687, censored 3,235, uncensored 6,452. Waldχ2=599.04

  2. Source: MicroReg based on EUSILC, 2016 (2016)

Data and code availability

The model is based on the Italian sample of EUSILC. Access to EUSILC data is granted by Eurostat to recognized research entities for scientific purposes only. Tax rules considered in this paper refer to the 2016 tax returns (tax year 2015) for both Italy and France. The EUSILC sample of 2016 is used.

The code of the model is proprietary.

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