An R package to identify, explore, and visualize Episodes of State Ownership Transformation (ESOT) using V-Dem data. The package detects privatization (movement towards a market economy) and statization (movement towards greater state ownership) episodes based on the V-Dem variable v2clstown_osp (State Ownership of the Economy, 0–4 scale).
Note: This package is built upon the methodology and codebase of the ERT — Episodes of Regime Transformation package, developed by the V-Dem Institute. The episode-detection algorithm is directly adapted from ERT's approach to identifying regime transitions, scaled and re-oriented for economic ownership dynamics. Full credit for the original framework goes to the ERT authors (see Citation).
# Install the development version from GitHub
# (requires the devtools package)
install.packages("devtools")
devtools::install_github("your-username/ESOT")Make sure you have an up-to-date R installation and the appropriate build tools:
- Windows: Rtools
- macOS: Xcode Command Line Tools
- Linux:
r-base-dev
The package uses the V-Dem variable v2clstown_osp (State Ownership of the Economy), which ranges from 0 (high state ownership / planned economy) to 4 (low state ownership / market economy).
Economy types are derived as follows:
| Value range | Economy type |
|---|---|
v2clstown_osp < 1 |
Planned economy (0) |
1 ≤ v2clstown_osp < 2 |
State-dominated mixed economy (1) |
2 ≤ v2clstown_osp < 3 |
Market-dominated mixed economy (2) |
v2clstown_osp ≥ 3 |
Market economy (3) |
Identifies episodes of privatization and statization for all countries in the most recent V-Dem dataset.
# Get episodes with default parameters
episodes <- get_eps()
# Customize thresholds
episodes <- get_eps(start_incl = 0.04,
cum_incl = 0.4,
year_turn = 0.12,
cum_turn = 0.4,
tolerance = 5)Parameters (all scaled to the 0–4 range of v2clstown_osp, following ERT's methodology):
| Parameter | Description | Default |
|---|---|---|
start_incl |
Minimum annual change to trigger an episode onset | 0.04 |
cum_incl |
Minimum cumulative change to qualify as a manifest episode | 0.4 |
year_turn |
Annual change in opposite direction to trigger episode termination | 0.12 |
cum_turn |
Cumulative change in opposite direction to trigger termination | 0.4 |
tolerance |
Number of years of tolerance for stasis or reverse movement | 5 |
Episode outcomes — Privatization:
| Code | Outcome |
|---|---|
| 1 | Market transition |
| 2 | Preempted market transition |
| 3 | Stabilized planned economy |
| 4 | Reverted privatization |
| 5 | Deepened market economy |
| 6 | Uncertain outcome |
Episode outcomes — Statization:
| Code | Outcome |
|---|---|
| 1 | Market collapse |
| 2 | Preempted market collapse |
| 3 | Diminished market economy |
| 4 | Averted statization |
| 5 | Deepened planned economy |
| 6 | Uncertain outcome |
Checks for and reports overlapping privatization and statization episodes.
overlap <- find_overlap()Plots privatization and statization episodes over time for a selected country.
# Plot episodes for Russia between 1950 and 2010
plot_episodes(country = "Russia", years = c(1950, 2010))
# Plot in Spanish
plot_episodes(country = "Venezuela", years = c(1960, 2023), lang = "es")Plots the global number or share of countries undergoing privatization or statization episodes per year.
# Absolute number of countries
plot_all(abs = TRUE, years = c(1950, 2023))
# Share of countries (%)
plot_all(abs = FALSE, years = c(1950, 2023))
# In Spanish
plot_all(lang = "es")Both plot_episodes() and plot_all() support localized labels via the lang argument:
| Language | Code |
|---|---|
| English | "en" (default) |
| Spanish | "es" |
If you use the ESOT package, please cite both this package and the original ERT framework on which it is based:
ESOT package:
Maerz, Seraphine, Amanda Edgell, Joshua Krusell, Laura Maxwell, and Sebastian Hellmeier. ESOT — Episodes of State Ownership Transformation R package. 2025.
Original ERT framework (required credit):
Maerz, Seraphine, Amanda Edgell, Joshua Krusell, Laura Maxwell, and Sebastian Hellmeier. ERT — Episodes of Regime Transformation R package. Varieties of Democracy (V-Dem) Project. 2025. https://github.com/vdeminstitute/ERT
V-Dem dataset:
Coppedge, Michael et al. V-Dem Dataset. Varieties of Democracy (V-Dem) Project. https://www.v-dem.net
GPL-3