**Figure 1: The RUSMOD policy spine (order of simulations in the model)**

|Net market income (formal and informal earnings, investment incomes, private transfers and income from<br>subsistence farming)|
|---|
|+Simulated Employer andSelf-employed social insurance contributions(SIC)|
|+Simulated Personal income tax(PIT),incl. standard tax allowances|
|=Gross market income|
|-Simulated Employer andSelf-employedSIC|
|- Direct taxes(simulated PIT,not simulatedSocial tax allowance for thepreviousyear, property &vehicle taxes)|
|+ Not simulated benefits (public pensions, unemployment benefit, unified cash payment, housing privileges,<br>scholarships)|
|+ Simulated not means-tested benefits (childbirth grant, maternity allowance, childcare allowance up to 1.5 years,<br>compensation of childcare costs toparents,maternitycapital)|
|+ Simulated means-tested benefits (child allowance up to 16(18) years, allowance for the third child up to 3 years,<br>state social assistance,housingsubsidy)|
|=Disposable income|
|-Value added tax(VAT)|
|- Excise duties on alcohol,tobacco and car fuel|
|=Consumable or Post-Fiscal income|

The output of the model has been validated against official statistics (national accounts and administrative data) to assess the robustness of the model and its applicability for policy analysis, following the EUROMOD standards. To ensure comparability with the external sources some assumptions were used in the model. In general, although our modeling reflects as close as possible the existing statutory rules, in the baseline scenario we opted for computing economic rather than statutory incidence of taxes and benefits. Overall, the final estimates of poverty and inequality from RUSMOD are close to those based on national accounts; hence the model can be seen as a reliable tool for evaluating the current performance of the Russian tax-benefit system and the distributive impact of potential tax-benefit reforms.

# **Input data**

In order to be used within the EUROMOD framework, the input data set has to meet certain requirements (Figari, et al., 2007). A number of national household surveys have been considered for this purpose, but only one fulfilled all the essential criteria: the Russian Longitudinal Monitoring Survey of the Higher School of Economics (RLMS-HSE), an annual, nationally-representative survey that began in 1994 (see Table A-2 in the Annex for an overview of the input data). RLMS-HSE is a standard multi-topic survey with an extended set of information on economic well-being and health status. It collects individual level information on demographic characteristics, within-family relationships, labor market status, primary income by source, social benefits, expenditure, as well as other characteristics relevant for assessing tax liabilities or benefit entitlements. The survey satisfies international standards in terms of sampling and quality of data collection. The sample includes both cross-sectional and panel components. In geographical terms it covers 32 (out of 80+) regions, however it is not representative at the regional level, with the exception for the two biggest cities – Moscow and St. Petersburg.

To account for time inconsistency between the input data (2016) and the policy year (2017), updating (or uprating) factors are used. Each monetary variable is updated so as to account for changes that have taken place between the year of the data and the year of the simulated tax-benefit system. Updating factors are generally based on changes in the average value of an income component 7