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Russian Crime Victimization Survey (RCVS)

License: CC BY 4.0         Dataverse     R

This replication package accompanies the paper. It documents steps to prepare a pooled dataset, and produces figures in the paper about RCVS.

The Russian Crime Victimization Survey (RCVS): harmonized pooled data from three nationally representative cross-sections (2018, 2021, 2024) and a longitudinal component (2021–2024). The RCVS is the only repeated nationwide victimization survey in Russia.

— The survey is conducted triennially (every three years) and is representative at the national level.

— The target population includes the entire adult population of Russia, regardless of citizenship status.

— The survey is administered via telephone using the CATI mode (Computer-Assisted Telephone Interviewing).

— Each cross-section wave employs Random Digit Dialing (RDD).

— The sample includes both victims and non-victims of crime.

— Across the three waves (2018, 2021, 2024), a total of 42,572 respondents were interviewed, with 3,456 re-interviewed as part of a panel (longitudinal) sample (2021–2024).

Questionnaire and Screening Logic

Line plot of number of filing by month


Data

Underlying RCVS data are available in three Harvard Dataverse repositories. This repository already contains copy of needed datasets from these repositories.

— Russian Crime Victimization Survey 2018

— Russian Crime Victimization Survey 2021

— Russian Crime Victimization Survey 2024

This replication package produces a pooled dataset, also available on Harvard Dataverse:

— Russian Crime Victimization Survey: Pooled Cross-Sections 2018, 2021, 2024, and Panel 2021–2024

Paper

See the preprint. It contains a detailed description of the survey methodology, including internal and external validation, the procedure for calculating post-stratification weights for the cross-sectional subsample, and the correction for non-response bias (attrition) in the panel sample.

Usage Notes

The replication package recreates a harmonized pooled dataset that combines 2018-2024. It saves the resulting dataset in various formats and accompanying codebooks in /results folder. It also recreates figures used in the paper and saves them into /figures folder.

Quick start

This will download the archive of this repository, unzip it into the folder rcvs-main, and replicate the code.

download.file(url = "https://github.com/irlcode/RCVS/archive/master.zip", destfile = "rcvs.zip")
unzip(zipfile = "rcvs.zip")
source("rcvs-main/code/00_master_script.R")

Manual

  1. Download the repository: scroll up, find and click green button <>Code -> Download ZIP. Download and unzip.
  2. Run 00_master_file.R within /code folder.

It will sequentially execute scripts to preprocess and merge datasets, and then reproduce the figures from the outputted dataset.

Partially reproducible scripts

Several scripts used for preparing survey weights and raking are not fully reproducible due to data limitations. We publish them in the folder 04_non_reproducible. Scripts for processing official Rosstat data used for bias estimation and weighting.

— Demographics: 04a_extract_age_region_distributions.r and 04b_extract_educ_distribution.R extract population moments from Rosstat yearbooks and the 2020 Census to compute post-stratification weights.

— CMLC (KOUZH): 04c_prepare_kouzh_data.r processes the Comprehensive Monitoring of Living Conditions (2018–2024). Due to the prohibitive size of raw files, we provide the processed outputs in data/auxdata/.

— Panel Attrition: 04e_define... and 04f_compute... handle attrition corrections between 2021 and 2024. Contact propensity estimation requires survey paradata (call attempts), which are currently non-public.

Victimization trends

These figures from the paper are produced by script code/02_produce_figures.R:

Dynamics of Victimization in Russia, 2018–2024

Line plot of dynamics of Victimization in Russia, 2018–2024

Annual Adult Victimization by Crime Types in Russia over 2018–2024

Line plot of Annual Adult Victimization by Crime Types in Russia over 2018–2024

Structure of repository

├── code
│   ├── 00_master_script.R
│   ├── 01a_gather_repeated_crosssections.R
│   ├── 01b_gather_panel.R
│   ├── 01c_attach_deflators.R
│   ├── 01d_attach_panel_weights.R
│   ├── 01e_export_data.R
│   ├── 01f_prepare_english_version.R
│   ├── 01g_rendering_codebooks.R
│   ├── 02_produce_figures.R
│   ├── 03_power_analysis.R
│   ├── 04_non_reproducible
│   │   ├── 04a_extract_age_region_distributions.r
│   │   ├── 04b_extract_educ_distribution.R
│   │   ├── 04c_prepare_kouzh_data.r
│   │   ├── 04d_raking_weights_for_crosssection.r
│   │   ├── 04e_define_final_dispositions_codes.R
│   │   └── 04f_compute_weights_for_cohort.r
│   └── aux_code
│       ├── codebook_pooled_data_eng.Rmd
│       ├── codebook_pooled_data_rus.Rmd
│       ├── codebook_variables_changes_eng.Rmd
│       ├── codebook_variables_changes_rus.Rmd
│       ├── img
│       │   ├── eusp_logo_eng.png
│       │   ├── eusp_logo.png
│       │   ├── ipp_logo_eng.png
│       │   └── ipp_logo.png
│       └── R_function_ci4prev.r
├── data
│   ├── auxdata
│   │   ├── computed_panel_weights_13mar26.rdata
│   │   ├── computed_raking_weights_17apr25.rdata
│   │   ├── federal_district_population_educ.csv
│   │   ├── federal_district_population_sex_agegroup_yearly.csv
│   │   ├── kouzh_18_20_22_24_5sep25.rdata
│   │   ├── kouzh_victim_24.rdata
│   │   ├── official_crime_rate.xlsx
│   │   ├── region_educ_population_census.csv
│   │   └── region_sex_age_yearly_population_2018_2024.csv
│   ├── rcvs_2018_dataset_2026-03-14.Rds
│   ├── rcvs_2021_dataset_2026-03-14.Rds
│   ├── rcvs_panel_2024_2026-03-14.Rds
│   ├── rcvs_rdd_2024_2026-03-14.Rds
│   └── supplementary_data
│       ├── all_var_names_fixed.csv
│       ├── codebook_all_waves_eng.csv
│       ├── codebook_all_waves_rus.csv
│       ├── codebook_panels_eng.csv
│       ├── english_version
│       │   ├── all_waves_values.xlsx
│       │   ├── all_waves_variables.xlsx
│       │   ├── panels_values.xlsx
│       │   ├── panels_variables.xlsx
│       │   └── rcvs_regions_iso_keys.xlsx
│       ├── key_pairs_panel.csv
│       ├── key_pairs_rdd.csv
│       ├── panels_var_names_fixed.csv
│       └── qof_changes.csv
├── figures
│   ├── age_plot.png
│   ├── crimetype_plot.png
│   ├── prevalence_plot.png
│   └── rcvs_flow.png
└── README.md

ToDo

  • Computing weights for combining the 2024 refreshment (cross-sectional) and panel samples (Watson, 2014, Watson, Lynn, 2021).
  • Calculating wave-specific post-stratification weights for each cross-sectional sample.

Licence

Creative Commons License
Creative Commons License Attribution 4.0 International (CC BY 4.0).

Citation

Please cite as:

Kuchakov, R., Serebrennikov, D., Bobrikov, D., Knorre, A., & Skougarevskiy, D. (2026). Russian Crime Victimization Survey: Pooled Cross-Sections and a Longitudinal Panel, 2018–2024 (SSRN Scholarly Paper No. 6418058). Social Science Research Network. http://dx.doi.org/10.2139/ssrn.6418058

@article{kuchakov2026rcvs,
  title={{R}ussian {C}rime {V}ictimization {S}urvey: {P}ooled {C}ross-{S}ections and a {L}ongitudinal {P}anel, 2018–2024},
  author={Kuchakov, Ruslan and Serebrennikov, Dmitriy and Bobrikov, Dmitriy and Knorre, Alex and Skougarevskiy, Dmitriy},
  journal={Social Science Research Network (SSRN)},
  doi={http://dx.doi.org/10.2139/ssrn.6418058},
  year={2026},
}

Contacts

Ruslan Kuchakov, rkuchakov@eu.spb.ru