Conditionality
The IMF Conditionality Dataset records the policy conditions attached to IMF lending programs in 1980–2019: 65,894 conditions in 134 countries. They are taken from the Letters of Intent and Memoranda of Economic and Financial Policies that borrowing governments draft with IMF staff, found in IMF Executive Board documents and Country Reports. Each condition is classified by type—prior action, structural benchmark, quantitative or structural performance criterion, or indicative benchmark—and into one of 13 policy areas. The main dataset gives yearly indicators for 220 countries and territories; the raw dataset lists each condition. The codebook explains how the data were collected, coded, and combined.
At a glance
- Coverage
- 1980–2019; conditions in 134 countries
- Version
- October 2026
- Unit of observation
- Country-year-condition (raw dataset); country-year (main dataset)
- Status
- Available
Downloads
- Codebook (IMFMonitor_Conditionality_Codebook.pdf)Download
PDF · 586 KB · October 2026 - Main dataset (IMFMonitor_Conditionality_Main.zip)Download
Country-year indicators: counts of conditions by type and policy area, and measures adjusted for waivers and program interruptions.
Stata (.dta) in ZIP · 234 KB · October 2026 - Raw dataset (IMFMonitor_Conditionality_Raw.xlsx)Download
One row per condition and year, with the condition’s text, type, policy area, implementation status, and source document.
Excel (.xlsx) · 3.3 MB · October 2026 - Reviews dataset (IMFMonitor_Reviews.xlsx)Download
One row per program review, with the date the Executive Board concluded it and the date proposed for the next; the code uses it to adjust conditions for program interruptions.
Excel (.xlsx) · 230 KB · October 2026 - Code (IMFMonitor_Conditionality_Code.zip)Download
The Stata do-file that builds the main dataset from the raw dataset and the reviews dataset (IMFMonitor_Reviews.xlsx), with the World Bank income-group file it uses.
Stata do-file and World Bank income groups (.xls) in ZIP · 68 KB · October 2026
How to cite
Kentikelenis, A. & Stubbs, T. (2023). A Thousand Cuts: Social Protection in the Age of Austerity. Oxford University Press.
Figures
Publications using the data
- Kentikelenis, A. & Stubbs, T. (2023). A Thousand Cuts: Social Protection in the Age of Austerity. Oxford University Press. https://doi.org/10.1093/oso/9780190637736.001.0001
- Reinsberg, B., Stubbs, T., & Bujnoch, L. (2023). Structural adjustment, alienation, and mass protest. Social Science Research, 109, 102777. https://doi.org/10.1016/j.ssresearch.2022.102777
- Kentikelenis, A. & Stubbs, T. (2022). Austerity redux: The post-pandemic wave of budget cuts and the future of global public health. Global Policy, 13(1), 5–17. https://doi.org/10.1111/1758-5899.13028
- Reinsberg, B., Stubbs, T., & Kentikelenis, A. (2022). Compliance, defiance, and the dependency trap: International Monetary Fund program interruptions and their impact on capital markets. Regulation & Governance, 16(4), 1022–1041. https://doi.org/10.1111/rego.12422
- Reinsberg, B., Stubbs, T., & Kentikelenis, A. (2022). Unimplementable by design? Understanding (non-)compliance with International Monetary Fund policy conditionality. Governance, 35(3), 689–715. https://doi.org/10.1111/gove.12605
- Reinsberg, B., Kentikelenis, A., & Stubbs, T. (2021). Creating crony capitalism: Neoliberal globalization and the fueling of corruption. Socio-Economic Review, 19(2), 607–634. https://doi.org/10.1093/ser/mwz039
- Reinsberg, B., Stubbs, T., & Kentikelenis, A. (2020). Taxing the people, not trade: The International Monetary Fund and the structure of taxation in developing countries. Studies in Comparative International Development, 55(3), 278–304. https://doi.org/10.1007/s12116-020-09307-4
- Reinsberg, B., Stubbs, T., Kentikelenis, A., & King, L. (2020). Bad governance: How privatization increases corruption in the developing world. Regulation & Governance, 14(4), 698–717. https://doi.org/10.1111/rego.12265
- Stubbs, T., Reinsberg, B., Kentikelenis, A., & King, L. (2020). How to evaluate the effects of IMF conditionality: An extension of quantitative approaches and an empirical application to public education spending. Review of International Organizations, 15(1), 29–73. https://doi.org/10.1007/s11558-018-9332-5
- Reinsberg, B., Kentikelenis, A., Stubbs, T., & King, L. (2019). The world system and the hollowing out of state capacity: How structural adjustment programs affect bureaucratic quality in developing countries. American Journal of Sociology, 124(4), 1222–1257. https://doi.org/10.1086/701703
- Reinsberg, B., Stubbs, T., Kentikelenis, A., & King, L. (2019). The political economy of labor market deregulation during IMF interventions. International Interactions, 45(3), 532–559. https://doi.org/10.1080/03050629.2019.1582531
- Stubbs, T., Kentikelenis, A., Stuckler, D., McKee, M., & King, L. (2017). The impact of IMF conditionality on government health expenditure: A cross-national analysis of 16 West African nations. Social Science & Medicine, 174, 220–227. https://doi.org/10.1016/j.socscimed.2016.12.016
- Kentikelenis, A., Stubbs, T., & King, L. (2016). IMF conditionality and development policy space, 1985–2014. Review of International Political Economy, 23(4), 543–582. https://doi.org/10.1080/09692290.2016.1174953
- Stubbs, T., Kentikelenis, A., & King, L. (2016). Catalyzing aid? The IMF and donor behavior in aid allocation. World Development, 78, 511–528. https://doi.org/10.1016/j.worlddev.2015.10.010
Version history
October 2026
Removes the 21 program participation indicators added in March 2026: program participation is now recorded in the Programs dataset. The data are otherwise unchanged, and the main and raw datasets are identical to those of July 2023. The codebook drops its sections on program participation and the programs dataset, and the code no longer needs the programs file.
Current release: its files are under Downloads.
March 2026 (v2.1)
Adds 21 indicators of IMF program participation to the main dataset: the number of months a program was in force in each year, and several yes-or-no measures of whether one was in force, each for all, concessional, and non-concessional programs. The codebook gains sections on these indicators and on the programs dataset, and a note on grouping the policy areas into broader categories. All other variables, and the raw dataset, are unchanged from July 2023.
- Codebook (v2026-03_IMFMonitor_Conditionality_Codebook.pdf)Download
PDF · 601 KB - Main dataset (v2026-03_IMFMonitor_Conditionality_Main.zip)Download
Stata (.dta) in ZIP · 241 KB - Code (v2026-03_IMFMonitor_Conditionality_Code.zip)Download
Stata do-file and World Bank income groups (.xls) in ZIP · 69 KB
July 2023 (v2.0)
Extends coverage from 1980–2014 to 1980–2019, and from 216 to 220 countries and territories, with 65,894 conditions in all. It also revises the coding of some conditions from 1980–2014: for example, structural performance criteria in 2009 are no longer recoded as structural benchmarks, and conditions from previously embargoed documents are added. The codebook’s section on dataset updates lists each change. This release’s files are not offered separately: its main and raw datasets are identical to those of October 2026.
September 2017 (v1.0)
First release, covering 1980–2014 for 216 countries and territories, with 58,406 conditions in the main dataset. Its codebook asks users to cite Kentikelenis, Stubbs, and King (2016).