regression is lower given that to date only a limited number of countries have undertaken repeat PEFA assessments. Running a robustness check using the CPIA indicator for PFM quality (CPIA-13), the results are similar with regards to a significant and negative relationship with initial PFM quality (albeit somewhat smaller). In addition, a strong negative effect of the change in population becomes significant, suggesting that countries with faster population growth have done worse with regards to improving the quality of their PFM systems. Furthermore, the fact that resource dependence does not show a significant relationship with in the first difference analysis using PEFA data, and a weak and barely significant relationship using CPIA data, implies that being resource dependent does not prevent a country from progressing with PFM reforms relative to progress seen in other countries—which is encouraging. Still, due to data constraints there is greater uncertainty regarding this finding, and the analysis should be revisited as repeat PEFA assessments for additional countries and time periods become available.

Both the cross-sectional and first-difference findings suggest that to some extent, differences in levels and changes in PFM performance are associated with country characteristics; while only a few variables combine high statistical significance (at the 1 percent level or higher) and a tangible impact. To understand more about why PFM reforms progress in some countries but less so in others despite similar broad characteristics, such as having a similar income level and regime type, we will need to shift from large N analysis using standardized data to comparative case studies that allow analyzing specific factors, and the dynamic interaction between institutional development and stakeholders to explore whether these account for such differences.

For the third research question, a preliminary investigation is conducted into the relationship between PFM quality and key fiscal outcomes, including cost-effectiveness in the use of funds for public service delivery (technical or operational efficiency). Findings validate that better public financial management is associated with lower variances in overall budget execution rates as well as cross-sector variance (robust when controlling for GDP per capita), but not with lower deficits. Furthermore, we do not find a correlation between PFM quality and public service delivery outcomes in health or education relative to these sectors’ fiscal allocations— that is, available data do not show a significant relationship with the operational efficiency of spending.<sup>4</sup> Given the data limitation discussed in the main sections, this part of the analysis needs to be interpreted with the greatest care.

The findings of this paper should be interpreted cautiously due to potential endogeneity and OVB. We do undertake various robustness tests in an effort to account for potential measurement error and OVB, including a variety of specifications and alternative sources of data. Regardless, the findings should not be interpreted as evidence of the direction of causality and more testing of alternative model specifications is needed.

This paper is the first part of a wider study on _Making reforms of PFM work: political economy aspects of buy-in and follow-through_ , aimed at exploring the role played by political economy factors in enabling or hindering PFM reforms and their effective implementation. It is increasingly recognized that such factors play a crucial role in differentiating whether and to what extent PFM reforms succeed. In this first part, the focus is on empirical analysis of country

> 4 These findings are consistent with Vlaicu et al. (2014) and World Bank (2013) which focus on the impact of a specific component of PFM systems—medium-term expenditure frameworks—on fiscal performance.

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