Figures and tables in Accounting for Behavioral Effects in Microsimulation: A Reduced Form Approach

Abstract

Microsimulation models are used worldwide to assist in the policy-making of governments. The simulation models may be purely non-behavioral or they may also include modules that simulate labor supply responses to the policy change in question. The present paper demonstrates how the practitioner can employ exogeneously given response estimates to account for behavioral effects in this type of work. Response estimates are combined with individual changes in work incentives at both the extensive and intensive margins. The concepts of the participation tax rate (PTR) and the effective marginal tax rate (EMTR) are employed. In the empirical illustration we discuss distributional and social welfare effects arising from the changes in Finnish taxes and benefits that took effect in 2020.

This article contains 10 figures and 9 tables.

Figures

**Figure 1.** Kernel density distributions of participation tax rates simulated with the baseline and reform legislations.

**Figure 2.** Kernel density distributions of effective marginal tax rates simulated with the baseline and reform legislations.

**Figure 3.** The average change (pp) of effective marginal tax rates annual earned income.

**Figure 4.** The policy effects (%) on disposable income by income decile.

**Figure 5.** The differences (pp) between behavioral and non-behavioral effects by income decile.

**Figure 6.** The policy effects (%) of various specifications on disposable income by income decile.

**Figure B1.** The differences (pp) in the effect of extensive margin responses in relation to the default specification (=0) by income decile.

**Figure B2.** The differences (pp) in the effect of intensive margin responses in relation to the default specification (=0) by income decile.

**Figure B3.** The differences (pp) in the effect of behavioral responses in relation to the baseline specification (=0) by income decile.

**Figure C4.** Effective marginal tax rates (%) by annual earned income with the baseline and reform legislations.

Tables

Table 1. PTR change by benefit receipt.

	Freq	PTR baseline	PTR reform	Change, pp
Flat rate UB	280 000	62.7%	62.9%	0.1
Earnings-related UB	270 000	69.3%	69.7%	0.4
Home care allowance	100 000	54.8%	54.7%	-0.1
Employed	1 890 000	66.6%	67.2%	0.5
Total	2 540 000	66.0%	66.5%	0.5

Note: If individual have several income sources within a year the following prioritization is used: 1. Home care allowance, 2. Earnings-related UB and 3. Flat rate UB. Employed are individuals with positive labor income and not received home care allowance or any unemployment benefit within a year. Baseline refers to legislation of year 2019 and reform to legislation of year 2020.

Table 2. Extensive margin responses.

	Default	Heterogenous
	Default	elasticity
PTR increase (pp.-change)	0.5	0.5
Population with increase	2,260,000	2,260,000
PTR decrease (pp.-change)	- 0.3	- 0.3
Population with decrease	270,000	270,000
Employment increase (person years)	200 (100 – 300)	200
Employment decrease (person years)	- 5,800 (-2,900 – -8,800)	- 5,700
Net change (person years)	- 5,700 (-2,800 – -8,500)	- 5,500

Note: Results are calculated with consumer price index and using the aggregate participation elasticity of 0.2. In heterogeneous elasticity column the aggregate participation elasticity is weighted using 8 different groups. The changes in PTR are the average changes and the values in brackets are formed using elasticities of 0.1 (LHS) and 0.3 (RHS). Values of employment changes are rounded to 100 units. Values of population with increase or decrease are rounded to 10,000 units.

Table 3. Changes in incentives and earnings in intensive margin with various specifications.

	Default	Extra income
	Default	of 6,000 euros/year
EMTR increase (pp-change)	1.0	0.6
Population with increase	1,920,000	1,920,000
EMTR decrease (pp-change)	-3.0	-1.2
Population with decrease	350,000	390,000
Earnings increase (Me)	120 (60 – 180)	40
Earnings decrease (Me)	- 250 (-130 – -380)	- 190
Net change (Me)	- 140 (-70 – -200)	- 150

Note: Default results are calculated with extra income of 1,200 euro/year. All cases are calculated using consumer price index. Values in brackets are calculated using elasticities of 0.1 (LHS) and 0.3 (RHS). Me refers to millions of euro. Values of earnings changes are rounded to 10 million euros. Values of population with increase or decrease are rounded to 10,000 units.

Table 4. Policy effects on inequality and poverty indicators.

	Base level in 20	Non-behavioral	Extensive margin	Intensive margin	Both margins	Total effect
Gini coefficient	28	-0.3	0.0	0.0	0.0	-0.3
Equalized income
Median	24,335	54	-29	-17	-47	7
At risk of poverty
Whole population (%)	13.4	-0.6	0.0	0.0	0.0	-0.6
Whole population (N)	738,000	-32,500	2,000	-200	1,600	-30,900
Children (%)	12.6	-0.4	0.1	0.0	0.1	-0.4
Children (N)	133,600	-4,600	600	100	600	-3,900
Elderly (%)	12.7	-1.4	0.0	0.0	0.0	-1.4
Elderly (N)	150,100	-16,200	0	0	0	-16,200
Fiscal changes
Taxes (Me)	35,700	130	-40	-70	-110	20
Benefits (Me)	13,600	360	90	0	90	450
Taxes-benefits (Me)	22,100	-230	-140	-70	-210	-430

Note: Results are calculated with consumer price index, elasticities of 0.2 and extra income of 1 200 euro/year. Total effect is the sum of non-behavioral and behavioral effects. Extensive margin, intensive margin and both margins are calculated compared to the reform’s (2020) non-behavioral simulation. Non-behavioral and total effect are calculated compared to the base level results. Poverty line used is set to 60% of median income and it is fixed to the baseline (2019) level. Children are defined as individuals aged less than 18 years. Elderly are defined as individuals aged 65 or more. Changes of individuals in at risk of poverty are rounded to 100 individuals. Fiscal changes are rounded to 10 million euros and baseline values of taxes and benefits are rounded to 100 million euros.

Table 5. Social welfare effects.

	Base level	Difference to base
	in 2019	Non-behavior	Extensive	Intensive	Both margins
$100 \times A (0.5)$	7.2	-0.1	-0.1	-0.1	-0.1
$100 \times A (1)$	12.7	-0.2	-0.2	-0.2	-0.2
$100 \times A (2)$	22.9	-0.3	-0.3	-0.4	-0.4
Mean equivalized disp. income	27,796	46	25	29	8
	$S W F = [1 - A (e)] \bar{Y}$
$A (0.5)$	25,791	72	51	58	37
$A (1)$	24,254	94	74	84	63
$A (2)$	21,438	130	112	124	107

Note: Inequality of the base situation and the change after the reform (Upper panel), with or without behavioural reactions and with Atkinson index with inequality aver sion equal to 0.5, 1, or 2. The lower panel depicts social welfare and the change relative to the base situation.

Table 6. Social welfare effects, revenue neutral case

	Base level	Difference to base
	in 2019	Non-behavior	Extensive	Intensive	Both margins
$100 \times A (0.5)$	7.2	-0.1	-0.1	-0.1	-0.1
$100 \times A (1)$	12.7	-0.2	-0.1	-0.2	-0.2
$100 \times A (2)$	22.9	-0.4	-0.4	-0.4	-0.4
Mean equivalized disp. income	27,796	-14	-35	-31	-52
Mean disp. income,household level	38,503	0	-28	-22	-50
	$S W F = [1 - A (e)] \bar{Y}$
$A (0.5)$	25,791	9	-12	-5	-26
$A (1)$	24,254	29	9	19	-2
$A (2)$	21,438	91	73	85	68

Note: Inequality of the base situation and the change after the reform (Upper panel), with or without behavioural reactions and with Atkinson index with in equality aver-sion equal to 0.5, 1, or 2. The reform is made revenue neutral by levying an additional lump-sum tax to all individuals. The lower panel depicts social welfare and the change relative to the base situation.

Table A1. Regression coefficients for male wage prediction.

Males (y=log monthly wage)	Lone dwellers		Couples		Single parents		Two parent families		Others
	coeff	p-value	coeff	p-value	coeff	p-value	coeff	p-value	coeff	p-value
Intercept	7.455	0.000	7.200	0.000	7.710	0.000	6.863	0.000	7.642	0.000
Age	0.027	0.000	0.024	0.000	0.018	0.000	0.035	0.000	0.016	0.000
Age²	0.000	0.000	0.000	0.000	0.000	0.003	0.000	0.000	0.000	0.000
Field of education (ref. unknown or other)
Generic programmes	0.129	0.019	0.392	0.000	0.001	0.997	0.477	0.000	0.285	0.000
Education	-0.097	0.104	0.077	0.203	-0.252	0.453	0.029	0.575	0.036	0.677
Humanities and arts	-0.087	0.119	0.047	0.421	-0.219	0.506	0.059	0.246	0.112	0.160
Business and social sciences	0.058	0.291	0.260	0.000	-0.067	0.838	0.362	0.000	0.238	0.002
Natural sciences. mathematics	0.018	0.747	0.194	0.001	-0.074	0.821	0.218	0.000	0.184	0.022
Engineering and manufacturing	0.115	0.034	0.308	0.000	0.018	0.957	0.368	0.000	0.284	0.000
Agriculture and forestry	0.033	0.558	0.183	0.002	-0.028	0.931	0.254	0.000	0.174	0.028
Health and welfare	0.069	0.209	0.237	0.000	-0.066	0.840	0.266	0.000	0.269	0.001
Services	0.056	0.307	0.254	0.000	-0.042	0.897	0.300	0.000	0.242	0.002
Level of education (ref. doctoral or equivalent)
Unknown or primary	-0.404	0.000	-0.289	0.000	-0.645	0.051	-0.207	0.000	-0.333	0.000
Secondary	-0.471	0.000	-0.533	0.000	-0.619	0.000	-0.527	0.000	-0.547	0.000
Post-secondary non-tertiary	-0.339	0.000	-0.431	0.000	-0.430	0.000	-0.419	0.000	-0.491	0.000
Short-cycle tertiary	-0.306	0.000	-0.312	0.000	-0.373	0.000	-0.295	0.000	-0.350	0.000
Master’s or equivalent	-0.087	0.000	-0.062	0.001	-0.058	0.302	-0.017	0.210	-0.138	0.001
Ages of children
Less than 3 years (0/1)					-0.003	0.964	-0.002	0.797	-0.012	0.480
3-6 years (0/1)					0.020	0.525	0.004	0.421	-0.042	0.006
7-18 years (0/1)					-0.041	0.321	-0.018	0.002	-0.010	0.359
Region (ref. Lapland)
Uusimaa	0.041	0.001	0.094	0.000	0.132	0.000	0.121	0.000	0.067	0.007
Etelä-Savo	-0.076	0.000	-0.069	0.000	-0.059	0.168	-0.059	0.000	0.007	0.859
Pohjois-Savo	-0.056	0.000	-0.040	0.005	0.011	0.770	-0.042	0.001	0.020	0.549
Pohjois-Karjala	-0.085	0.000	-0.058	0.000	-0.046	0.262	-0.071	0.000	-0.031	0.417
Keski-Suomi	-0.044	0.003	-0.028	0.045	0.003	0.941	-0.017	0.162	-0.012	0.709
Etelä-Pohjanmaa	-0.084	0.000	-0.072	0.000	-0.030	0.455	-0.089	0.000	-0.067	0.067
Pohjanmaa	-0.062	0.000	-0.007	0.661	0.004	0.925	-0.029	0.028	-0.038	0.288
Keski-Pohjanmaa	-0.048	0.035	-0.033	0.120	-0.008	0.884	-0.033	0.058	-0.053	0.276
Pohjois-Pohjanmaa	-0.031	0.023	-0.030	0.024	-0.001	0.982	-0.011	0.320	0.009	0.771
Kainuu	-0.067	0.001	-0.055	0.007	0.009	0.857	-0.052	0.004	0.006	0.918
Varsinais-Suomi	-0.042	0.002	-0.012	0.344	-0.015	0.648	-0.016	0.151	-0.030	0.289
Satakunta	-0.012	0.425	0.009	0.524	0.054	0.132	0.003	0.790	0.023	0.490
Kanta-Häme	-0.016	0.297	-0.003	0.841	0.038	0.315	0.004	0.750	0.007	0.839
Pirkanmaa	-0.049	0.000	-0.005	0.703	0.032	0.319	0.004	0.731	-0.024	0.404
Päijät-Häme	-0.025	0.108	-0.011	0.466	0.071	0.073	-0.009	0.475	-0.008	0.807
Kymenlaakso	0.022	0.164	0.051	0.001	0.077	0.057	0.017	0.209	-0.009	0.805
Etelä-Karjala	-0.013	0.451	0.013	0.415	0.082	0.066	-0.008	0.617	0.003	0.945
Months in unemployment during the year (ref. more than 8)
Less than 3	0.192	0.000	0.164	0.000	0.293	0.018	0.160	0.000	0.131	0.012
3-5	0.105	0.002	0.081	0.064	0.225	0.073	0.054	0.187	0.063	0.252
6-8	0.033	0.417	-0.108	0.031	0.185	0.165	0.012	0.806	0.008	0.901
Employment days	0.063	0.000	0.076	0.000	0.074	0.000	0.076	0.000	0.052	0.000
(100) in prev. year	0.063	0.000	0.076	0.000	0.074	0.000	0.076	0.000	0.052	0.000
Existing debt (0/1)	0.113	0.000	0.082	0.000	0.135	0.000	0.096	0.000	0.121	0.000
Married (0/1)	0.066	0.000	0.027	0.000	0.081	0.000	0.045	0.000	0.060	0.000
Income of other hh members (log €)			0.007	0.000	-0.005	0.001	0.018	0.000	0.002	0.049

Table A2. Regression coefficients for female wage prediction.

Females (y=log monthly wage)	Lone dwellers		Couples		Single parents		Two parent families		Others
	coeff	p-value	coeff	p-value	coeff	p-value	coeff	p-value	coeff	p-value
Intercept	7.522	0.000	7.385	0.000	7.459	0.000	7.130	0.000	7.591	0.000
Age	0.016	0.000	0.016	0.000	0.015	0.000	0.022	0.000	0.008	0.000
Age²	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.113
Field of education (ref. unknown or other)
Generic programmes	0.372	0.000	0.338	0.000	0.259	0.000	0.399	0.000	0.408	0.000
Education	0.216	0.002	0.172	0.002	0.024	0.733	0.117	0.008	0.272	0.000
Humanities and arts	0.201	0.004	0.157	0.004	0.046	0.520	0.143	0.001	0.261	0.000
Business and social sciences	0.325	0.000	0.282	0.000	0.192	0.006	0.295	0.000	0.372	0.000
Natural sciences. mathematics	0.286	0.000	0.257	0.000	0.164	0.026	0.232	0.000	0.359	0.000
Engineering and manufacturing	0.349	0.000	0.313	0.000	0.234	0.001	0.346	0.000	0.366	0.000
Agriculture and forestry	0.257	0.000	0.247	0.000	0.115	0.115	0.222	0.000	0.288	0.000
Health and welfare	0.339	0.000	0.275	0.000	0.170	0.016	0.253	0.000	0.383	0.000
Services	0.249	0.000	0.192	0.000	0.104	0.141	0.195	0.000	0.301	0.000
Level of education (ref. doctoral or equivalent)
Unknown or primary	-0.338	0.000	-0.435	0.000	-0.481	0.000	-0.400	0.000	-0.398	0.000
Secondary	-0.607	0.000	-0.669	0.000	-0.593	0.000	-0.639	0.000	-0.695	0.000
Post-secondary non-tertiary	-0.503	0.000	-0.556	0.000	-0.499	0.000	-0.532	0.000	-0.568	0.000
Short-cycle tertiary	-0.448	0.000	-0.500	0.000	-0.416	0.000	-0.477	0.000	-0.540	0.000
Master’s or equivalent	-0.162	0.000	-0.192	0.000	-0.091	0.001	-0.147	0.000	-0.240	0.000
Ages of children
Less than 3 years (0/1)					0.064	0.001	0.072	0.000	-0.021	0.264
3-6 years (0/1)					0.021	0.044	0.023	0.000	0.005	0.729
7-18 years (0/1)					0.011	0.433	0.016	0.005	-0.012	0.242
Region (ref. Lapland)
Uusimaa	0.085	0.000	0.116	0.000	0.142	0.000	0.108	0.000	0.097	0.000
Etelä-Savo	-0.017	0.320	-0.029	0.022	0.014	0.575	-0.022	0.085	-0.001	0.987
Pohjois-Savo	-0.027	0.075	-0.006	0.560	0.030	0.170	0.007	0.546	-0.002	0.940
Pohjois-Karjala	-0.044	0.013	-0.019	0.120	0.017	0.491	-0.014	0.262	-0.007	0.819
Keski-Suomi	-0.040	0.008	-0.014	0.190	0.005	0.810	-0.024	0.025	0.009	0.749
Etelä-Pohjanmaa	-0.026	0.117	-0.019	0.121	0.009	0.698	-0.031	0.006	-0.009	0.767
Pohjanmaa	-0.053	0.002	-0.022	0.070	0.043	0.080	-0.046	0.000	-0.054	0.070
Keski-Pohjanmaa	-0.032	0.174	-0.024	0.146	0.005	0.864	-0.049	0.002	0.015	0.713
Pohjois-Pohjanmaa	-0.040	0.004	0.000	0.999	0.009	0.641	-0.004	0.659	0.016	0.537
Kainuu	-0.044	0.045	-0.023	0.134	0.030	0.363	0.001	0.936	-0.109	0.014
Varsinais-Suomi	-0.011	0.380	0.018	0.074	0.034	0.074	0.012	0.198	0.012	0.612
Satakunta	-0.023	0.134	-0.006	0.604	0.017	0.429	-0.003	0.772	-0.026	0.378
Kanta-Häme	0.007	0.663	0.030	0.009	0.065	0.004	0.029	0.011	0.018	0.552
Pirkanmaa	-0.012	0.364	0.017	0.082	0.053	0.005	-0.004	0.648	-0.009	0.701
Päijät-Häme	-0.013	0.379	0.014	0.228	0.050	0.023	-0.003	0.770	0.005	0.856
Kymenlaakso	-0.007	0.643	0.002	0.852	0.023	0.316	0.004	0.750	0.002	0.948
Etelä-Karjala	-0.013	0.460	0.001	0.960	0.019	0.452	-0.013	0.306	-0.013	0.730
Months in unemployment during the year (ref. more than 8)
Less than 3	0.013	0.796	0.042	0.462	0.059	0.418	0.038	0.509	0.109	0.207
3-5	-0.043	0.402	-0.007	0.901	-0.034	0.646	-0.028	0.628	0.084	0.348
6-8	-0.129	0.039	-0.116	0.088	-0.081	0.397	-0.109	0.124	-0.089	0.390
Employment days	0.062	0.000	0.058	0.000	0.053	0.000	0.048	0.000	0.057	0.000
(100) in prev. year	0.062	0.000	0.058	0.000	0.053	0.000	0.048	0.000	0.057	0.000
Existing debt (0/1)	0.079	0.000	0.062	0.000	0.103	0.000	0.068	0.000	0.075	0.000
Married (0/1)	0.023	0.015	0.007	0.048	-0.009	0.386	-0.002	0.572	-0.014	0.102
Income of other hh members (log €)			0.015	0.000	-0.003	0.000	0.016	0.000	0.000	0.964

Table B3. Heterogeneous weights for participation elasticity

		Women	Men
Age of the youngest children	Over 17 years or no children	1.28	0.92
	under 3 years old	1.32	0.92
	3 to 7 years old	1	0.68
	8 to 17 years old	0.84	0.56

Source: Own calculations based on Kotamäki and Kärkkäinen (2018)