Digital Readiness Regimes
Replication Package – Digital Readiness Regimes This repository contains the replication materials for the paper: “Digital readiness regimes and development dynamics: The role of governance and skills beyond connectivity”. This project investigates cross-c
Replication Package – Digital Readiness Regimes
This repository contains the replication materials for the paper: “Digital readiness regimes and development dynamics: The role of governance and skills beyond connectivity”.
This project investigates cross-country differences in digital development by introducing the concept of digital readiness regimes, understood as multidimensional configurations of:
- digital infrastructure,
- human capital,
- innovation capacity,
- and regulatory quality.
Sources:
The analysis combines macro-level indicators from:
- World Bank (WDI)
- ITU (ICT indicators, regulatory tracker)
- UNCTAD (FTRI index)
- UN Comtrade (trade structure)
All variables are documented in the Appendix of the paper.
The replication files reproduce the main empirical steps of the paper:
- Data construction
- assembling a country–year panel (2010–2023),
- merging indicators from multiple international sources,
- harmonizing country names and handling missing data.
- Clustering analysis
- standardization of variables,
- identification of digital readiness regimes using k-means clustering,
- validation using silhouette scores and robustness checks.
- Regime dynamics (STATA)
- construction of Markov transition matrices,
- estimation of persistence and mobility across regimes.
- Econometric analysis (STATA)
- multinomial logit models of regime membership,
- robustness checks (ordered logit, transition models, alternative specifications),
- computation of average marginal effects.
- Visualization (R)
- generation of figures (cluster plots, boxplots, transition heatmaps),
- visualization of marginal effects and model results,
- preparation of publication-ready graphs.
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Files are hosted on the source repository. Click download to access the full dataset.