Figures and tables in Dual income tax reform in Germany: A microsimulation approach

Abstract

This paper assesses the impact on household labor supply of a Dual Income Tax reform in Germany. It relies on GMOD, a population-based tax-benefit microsimulation model, and uses flexible mixed logit simulation estimators.

This article contains 1 figure and 8 tables.

Figures

Tables

T = 0	if v ≤ 7664
T = 883.74x² + 1500x	if 7665 ≤ v ≤ 12584
$T = (v - 12584) \frac{0.25}{1 + t} + 952$	if 12585 ≤ v ≤ 12585 + K
$T = 883.74 y^{2} + 1500 y + \frac{0.25}{1 + t} K$	if 12586 + K ≤ v ≤ 12739 + K
$T = 228.74 z^{2} + 2.397 z + 989 + \frac{0.25}{1 + t} K$	if 12740 + K ≤ v ≤ 52151 + K
$T = 0.42 (v - K) - 7914 + \frac{0.25}{1 + t} K$	if v ≥ 52152 + K

x	=	( v-7664)/10000
y	=	( v-7664-K )/10000
z	=	( v-12739-K )/10000

Table 1. Labor supply transition matrix for single men.

	Post-reform hours
Pre-reform hours	0	10	20	30	40	50	% (row)
0	16.55	0.00	0.01	0.26	0.56	0.20	17.59
10	0.00	2.12	0.00	0.04	0.05	0.08	2.29
20	0.00	0.00	1.79	0.01	0.02	0.04	1.85
30	0.00	0.00	0.00	17.43	0.20	0.13	17.77
40	0.01	0.00	0.00	0.01	42.05	0.24	42.30
50	0.00	0.00	0.00	0.00	0.03	18.18	18.21
% (column)	16.56	2.12	1.79	17.75	42.91	18.87	100.00

Source: Own calculations. Any summing errors are due to rounding.

Table 2. Labor supply transition matrix for single women.

	Post-reform hours
Pre-reform hours	0	10	20	30	40	50	% (row)
0	17.54	0.07	1.27	3.32	2.78	0.21	25.19
10	0.04	4.02	0.18	0.66	0.53	0.08	5.51
20	0.04	0.02	8.49	0.46	0.42	0.08	9.50
30	0.17	0.00	0.02	20.72	0.30	0.05	21.27
40	0.17	0.02	0.03	0.05	31.77	0.02	32.05
50	0.14	0.01	0.10	0.09	0.08	6.07	6.49
% (column)	18.11	4.13	10.09	25.29	35.88	6.50	100.00

Source: Own calculations. Any summing errors are due to rounding.

Table 3. Labor supply transition matrix for men in couples.

	Post-reform hours
Pre-reform hours	0	10	20	30	40	50	% (row)
0	9.41	0.00	0.01	0.03	0.08	0.06	9.59
10	0.00	0.48	0.00	0.00	0.00	0.00	0.49
20	0.00	0.00	1.00	0.00	0.01	0.00	1.02
30	0.03	0.00	0.00	16.38	0.10	0.10	16.61
40	0.08	0.00	0.02	0.12	50.31	0.13	50.66
50	0.04	0.00	0.01	0.05	0.18	21.35	21.62
% (column)	9.55	0.49	1.05	16.58	50.68	21.65	100.00

Source: Own calculations. Any summing errors are due to rounding.

Table 4. Labor supply transition matrix for women in couples.

	Post-reform hours
Pre-reform hours	0	10	20	30	40	50	% (row)
0	33.78	0.14	0.26	0.19	0.24	0.02	34.63
10	0.02	10.88	0.05	0.07	0.02	0.00	11.05
20	0.01	0.00	15.71	0.02	0.06	0.00	15.82
30	0.01	0.02	0.03	16.63	0.07	0.04	16.81
40	0.00	0.00	0.01	0.02	17.96	0.04	18.04
50	0.00	0.00	0.01	0.01	0.01	3.62	3.66
% (column)	33.83	11.05	16.07	16.95	18.37	3.73	100.00

Source: Own calculations. Any summing errors are due to rounding.

Table 5. Estimated preference parameters, singles.

	Single Men	Single Women
Income	0.0680	0.183**
	(0.0363)	(0.0630)
Income²	−0.000264	−0.00291*
	(0.000403)	(0.00121)
Leisure	0.371***	0.842***
	(0.0806)	(0.123)
Leisure²	−0.00287 ***	−0.00469 ***
	(0.000399)	(0.000496)
Leisure*income	−0.00128	−0.00233**
	(0.000653)	(0.000779)
Leisure*age	−0.00425	−0.0159**
	(0.00361)	(0.00536)
Leisure*age²	0.0000545	0.000205**
	(0.0000464)	(0.0000682)
Leisure*(East Germany?)	0.0218*	−0.00203
	(0.00872)	(0.00982)
Leisure*(Nursing case in family?)	0.0126	−0.00950
	(0.0240)	(0.0215)
Leisure*foreign?	0.0297**	−0.0209
	(0.0112)	(0.0190)
Leisure*(high education?)	−0.0355**	−0.0289**
	(0.0113)	(0.0104)
Leisure*(low education?)	0.0229**	0.0300*
	(0.00848)	(0.0147)
Leisure*handicapped?	0.0363**	0.00161
	(0.0133)	(0.0226)
Leisure*(no. of kids under 6)		0.0700 ***
		(0.0122)
Leisure*(no. of kids age 6-16)		0.0358 ***
		(0.00662)
Standard Deviation
Income	0.0902 ***	0.154***
	(0.0225)	(0.0307)
Observations	1116	1312
Standard errors in parentheses

p < 0.05.

p < 0.01.

p < 0.001.

Table 6. A description of the sample for 1997, 1998, and 1999.

	Coefficient	Std. Err.
Income	0.0644**	(0.0197)
Income²	0.0004954	(0.0000644)
Female’s leisure	0.486***	(0.108)
(Female’s leisure)	−0.00364 ***	(0.000661)
Male’s leisure	0.268*	(0.107)
(Male’s leisure)	−0.00319 ***	(0.000315)
(Female’s leisure)*(male’s leisure)	−0.000448	(0.000282)
(Female’s leisure)(female’sage)	−0.00333	(0.00360)
(Female’s leisure)(female’sage)²	0.0000542	(0.0000450)
(Female’s leisure)*(East Germany?)	−0.0434***	(0.00763)
(Female’s leisure)*(no. of kids under 6)	0.0701***	(0.0101)
(Female’s leisure)*(no. of kids aged 616)	0.0301 ***	(0.00492)
(Female’s leisure)*(nursing case in family?)	0.0346	(0.0181)
(Female’s leisure)*(married?)	0.0320**	(0.0108)
(Male’s leisure)(male’sage)	0.00514	(0.00470)
(Male’s leisure)(male’sage)²	−0.0000484	(0.0000555)
(Male’s leisure)*(East Germany?)	0.00857	(0.00881)
(Male’s leisure)*(no. of kids under 6)	0.00257	(0.00715)
(Male’s leisure)*(no. of kids aged 6-16)	0.000312	(0.00439)
(Male’s leisure)*(nursing case in family?)	0.0181	(0.0126)
(Male’s leisure)*(married?)	−0.0158	(0.0110)
Standard Deviation
Income	0.0745**
	(0.0233)
Sample Size	2015
Log-likelihood	−14161577

p < 0.05.

p < 0.01.

p < 0.001.

Note: A question mark means that the variable is binary, coded 1 for a “Yes” and 0 for a “No”.