IMF Working Papers

Expenditure Conditionality in IMF-supported Programs

By Sanjeev Gupta, Michela Schena, Reza Yousefi

December 7, 2018

Download PDF

Preview Citation

Format: Chicago

Sanjeev Gupta, Michela Schena, and Reza Yousefi. Expenditure Conditionality in IMF-supported Programs, (USA: International Monetary Fund, 2018) accessed November 8, 2024

Disclaimer: IMF Working Papers describe research in progress by the author(s) and are published to elicit comments and to encourage debate. The views expressed in IMF Working Papers are those of the author(s) and do not necessarily represent the views of the IMF, its Executive Board, or IMF management.

Summary

This paper studies the impact of expenditure conditionality in IMF programs on the composition of public spending. A granular dataset on different government expenditure conditions covering 115 countries for the 1992-2016 period is compiled. The results support the view that while conditionality on specific elements of spending could help achieve a program’s short-term objectives, it is structural conditionality which delivers lasting benefits. Structural public financial management conditionality (such as on budget execution and control) has proven to be effective in boosting the long-term level of education, health, and public investment expenditures. The results further indicate that conditionality on raising such spending may come at the expense of other expenditures. Finally, the successful implementation (and not mere existence) of the conditionality is crucial for improved outcomes. These findings are relevant for policy makers targeting achievement of the Sustainable Development Goals (SDGs).

Subject: Education spending, Expenditure, Health care spending, Public investment spending, Total expenditures

Keywords: Expenditure conditionality, WP

Publication Details

  • Pages:

    31

  • Volume:

    ---

  • DOI:

    ---

  • Issue:

    ---

  • Series:

    Working Paper No. 2018/255

  • Stock No:

    WPIEA2018255

  • ISBN:

    9781484389072

  • ISSN:

    1018-5941