1. Taxes and benefits
  2. Labour supply and demand
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The LOTTE System of Tax Microsimulation Models

  1. Zhiyang Jia
  2. Bodil M Larsen
  3. Bård Lian
  4. Runa Nesbakken
  5. Odd E Nygård
  6. Thor O Thoresen  Is a corresponding author
  7. Trine E Vattø
  1. Research Department, Statistics Norway, Norway
  2. Statistics Norway and Norwegian Fiscal Studies, the Department of Economics, Norway
Research article
Volume 17(3) Winter 2024
Cite this article as: Z. Jia, B. M Larsen, B. Lian, R. Nesbakken, O. E Nygård, T. O Thoresen, T. E Vattø; 2024; The LOTTE System of Tax Microsimulation Models; International Journal of Microsimulation; 17(3); 73-95. doi: 10.34196/ijm.00308
3 figures and 10 tables

Figures

Figure 1
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Overall structure of a LOTTE-Skatt tax-benefit model simulation
Figure 2
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Simulated average increase in the tax burden across pre-tax income in deciles. 1 percentage point increase in tax on ordinary income in 2023. In thousands of NOK
Figure 3
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Estimates of tax redistributional effects 1992–2004, based on the fixed-income approach for income bases 1992, 1998, and 2004

Tables

Table 1
Simulated revenue effects of a 1 percentage point increase in tax on ordinary income in 2023. In millions of NOK
AlternativeReferenceDifference
Income tax, municipal level237,079220,84016,238
Income tax, state level136,401136,4010
Social insurance tax178,102178,1020
Bracket tax100,732100,7320
Wealth tax, municipal level20,24820,2480
Wealth tax, state level9,7319,7310
- Tax red., housing savings scheme for young taxpayers5805800
- Tax red., pensioners13,17113,11061
- Tax red. in the north (North-Troms and Finnmark)1,1331,11914
Total taxes667,409651,24616,163
- Cash-for-care1,3771,3770
- Child benefit22,17122,1710
- Additional child benefit (small children, single parents)44440
Total643,817627,65416,163

  1. Notes: Standard output revenue table from a LOTTE-Skatt simulation. Simulation alternative compared to a 2023 reference using 2020 data (10% sample) projected to 2023.

Table 2
Simulated output from LOTTE-Skatt compared to output from the administrative registers based on income tax returns, 2021. In million NOK and percent
LOTTE-SkattTax reg.Diff. in %
Income tax, municipal level254,589254,1990.15
Income tax, state level122,580122,3820.16
Social insurance tax165,319164,8290.30
Bracket tax81,82981,7720.07
Wealth tax, municipal level14,98914,9110.52
Wealth tax, state level3,2123,1990.40
- Tax reduction, housing savings scheme for young taxpayers1,0030,9663.84
- Tax reduction, pensioners14,21314,229-0.11
- Tax reduction in the north (North-Troms and Finnmark)1,0691,0680.10
Total626,233625,0290.19

  1. Notes: Both the simulated output from LOTTE-Skatt and the output from administrative tax registers are based on the population of all residents in 2021.

Table 3
Simulated tax revenue effects of introducing a fifth tax bracket. Millions of NOK
Total tax revenueDiff. to benchmark
Benchmark: 2023 tax rules without a 5th bracket578,134-
2023 tax rules:
Direct (non-behavioral) effect578,402268
Intensive margin behavioral effect-106
Extensive margin behavioral effect-6
Direct and behavioral effects578,290156
Behavioral counteracting effect ratio0.42

  1. Notes: Simulations generated by the Norwegian tax-benefit model LOTTE-Skatt, data for 2020 projected to 2023. Behavioral effects are taken into account with an ETI estimate of 0.2 at the intensive margin and 0.1 at the extensive margin. Source: Jia et al. (2023).

Table 4
Simulated labor supply elasticities with respect to the wage rate for individuals, singles and in couples, 2014
FemaleMaleFemaleMale
Own wageOwn wageCross wageCross wage
Individuals in couple
 Participation (ext. margin)0.135--0.048-
 Hours cond. on working (int. margin)0.1970.095-0.043-0.009
 Total elasticity0.3320.095-0.091-0.009
Single individuals
 Participation (ext. margin)0.012-
 Hours cond. on working (int. margin)0.0570.009
 Total elasticity0.0690.009

  1. Notes: The elasticities reflect the simulated percentage change (average across individuals) in the probability of participation (extensive margin) and working hours conditional on working (intensive margin) when the hourly wage rate is increased by one percent for all wage earners. Note that due to high male participation rates, we do not estimate extensive margin responses for males.

Table 5
Estimates of self-financing ratios for a number of changes in rates, thresholds, allowances, and deductions, 2023. Percent
Tax changeSelf-financing ratio, pct
Reduced rate bracket tax, bracket 310
Increased threshold bracket tax, bracket 39
Reduced rate ordinary income6
Reduced rate social insurance tax5
Reduced rate bracket tax, bracket 24
Increased threshold bracket tax, bracket 22
Increased threshold for maximum deduction in minimum standard deduction1
Reduced rate bracket tax, bracket 10
Increased threshold bracket tax, bracket 10
Increased personal allowance0
Increased rate minimum standard deduction-16

  1. Notes: For a tax decrease, the self-financing ratio is the ratio between the effect on revenue due to labor supply adjustments and the initial static (or mechanical) revenue effect estimate (standard tax-benefit model calculation). Source: Finansdepartementet (2023).

Table 6
Average weekly hours of work, pre- and post-reform, derived from a simulation employing a labor supply model. Standard errors in parentheses
Pre-reform working hoursPost-reform working hoursDifference, %
Single females35.20 (0.321)35.27 (0.322)0.18
Single males38.95 (0.039)38.97 (0.040)0.04
Females in couple32.13 (0.068)32.25 (0.068)0.36
Males in couple38.60 (0.013)38.64 (0.014)0.11

  1. Notes: Standard errors are obtained by non-parametric bootstrapping, 30 repetitions. Source: Thoresen and Vattø (2015).

Table 7
Comparison of net-of-tax rate elasticity estimates obtained from labor supply model simulations and the ETI approach for working hours and earned income. Standard errors in parentheses
Discrete choice labor supply simulations, working hoursPanel data information
Working hoursEarned income
Single females0.018 (0.0005)0.032 (0.0037)0.020 (0.0051)
Single males0.062 (0.0027)0.023 (0.0055)0.039 (0.0054)
Females in couple0.026 (0.0001)0.051 (0.0046)0.031 (0.0045)
Males in couple0.015 (0.0005)0.016 (0.0059)0.053 (0.0034)
Weighted average0.026 (0.0012)0.028 (0.0053)0.041 (0.0043)

  1. Notes: The weighted averages are calculated by accounting for the number of observations in each group. Standard errors are obtained by using the delta method. Source: Thoresen and Vattø (2015).

Table 8
Consumption expenditure of different household types, five commodities (NOK in 2023)
Household typeFoodWineElectricityClothesAir travel
Singles31,4363,51515,66512,7983,439
Couples57,3357,77124,55134,2949,564
Couples with one child66,9427,47826,88141,8359,862
Couples with two children78,7137,67130,00350,76310,084
Couples, more than two children90,4256,47532,21355,96110,084
Others66,0456,75526,10136,9708,966
All households51,6175,73621,98628,4657,035

  1. Notes: Average household expenditure for different household types and consumer goods in 2023, obtained by the model LOTTE-Konsum. Children defined as individuals less than 18 years of age.

Table 9
Distribution of tax burden increase for five goods, tax burden increased by NOK 100 on average on each good
DecileFoodWineElectricityClothesAir travel
168764319
27931735634
38549816751
49062867564
59475918476
69989979390
7105107105104107
8112130114119128
9121163127141159
10148287163231281
All100100100100100

  1. Notes: All individuals are ranked according to total household expenditure divided by the number of household members in 2023. Change in tax burden is measured as change in real expenditure per household member due to a price increase on a specific good, where real expenditure is defined as total household expenditure divided by a household-specific price index. We change the tax burden for each good by NOK 100 on average by the use of the model LOTTE-Konsum.

Table 10
Summary of revenue-offsetting effects, tax cuts brought about by the Norwegian tax reform of 2006
Labor supply responsesMPCPersonal income tax, labor supplyDirect effect, commodity taxCommodity tax, labor supplyPayroll tax, labor supplyOverall offsetting effect
0.50.270.090.040.090.48
Low response0.70.270.120.050.090.53
0.90.270.150.060.090.58
0.50.340.090.050.120.59
Benchmark:0.70.340.120.060.120.64
middle response0.90.340.150.080.120.70
0.50.390.090.050.130.65
High response0.70.390.120.070.130.70
0.90.390.150.090.130.76

  1. Notes: Results are shown for three assumptions about labor supply effects (low, middle, and high) and for three assumptions about the marginal propensity to consume, MPC (0.5, 0.7, and 0.9). The overall offsetting revenue effect reflects contributions from labor supply alone, increased commodity taxation attributable to increased disposable income, and increased commodity and payroll tax due to labor supply adjustments. Source: Thoresen et al. (2010).

Data and code availability

The data referred to in this article are managed by Statistics Norway under the Norwegian Statistics Act. Transfer of personal data outside the country's borders is not allowed according to the Statistics Act. This means that any researcher or institution that wishes to apply for microdata will only be granted access to completely anonymous data. Due to the difficulty of anonymising data in such a small country as Norway, this will rarely be feasible. An alternative is to gain access to data through a Norwegian research institution. This requires that the participating members are pre-submitted to Statistics Norway and that the formal requirements are fulfilled.

We are currently recoding the model, also with the ambition to make the source code open.

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