The _resource_ dependency variable is a dummy variable capturing those countries classified as ‘resource rich’ if more than 20 percent of total revenues is derived from natural resources. We determined these classifications based on data and previous work of the International Monetary Fund.<sup>23</sup> Resource dependence is assumed to have negative impacts through a variety of channels, including reduced accountability between citizens and state elites, greater incentives for intransparency in the management of public funds, and the presence of windfall revenue as well as revenue volatility which might negatively affect budget planning and execution (de Renzio et al. 2009, Daban Sanchez and Helis 2013).

The _tax revenue_ variable measures the level of tax revenue as a percentage of GDP. This variable uses a database compiled by the International Monetary Fund’s Fiscal Affairs Department (drawing on GFS, WEO, and OECD data). Higher levels of domestic revenue would provide resources to governments to invest inter alia in better PFM systems. Moreover, as citizens pay more taxes, they expect governments to use these funds well and in ways that result in improved and expanded services (Moore 2004 and Prichard and Leonard 2010). This should incentivize governments to invest in PFM systems that facilitate delivery of results and enable greater accountability. The connection rests on the assumption that the tax revenue derives from citizens rather than from natural resource wealth, since the latter may undermine rather than strengthen accountability relationships (see Andrews 2010 and Auty 2000). The main variable we use includes mainly non-resource related forms of revenue.<sup>24</sup> The _aid_ variable measures the level of official development assistance as a fraction of GNI. The source is the World Bank’s World Development Indicators, which contains, among other things, all of the official loans and grants received by developing countries from multilateral or bilateral sources.<sup>25</sup> For this variable, there are two related but somewhat contradictory expectations. One is that aid dependent countries are more likely to undertake public sector (including PFM) reforms (Therkildsen 2000 and 2001; see also Fialho Lopes and Fritz 2012), or that there is possibly even a reverse causation with donors investing more in countries that show greater effort and success with reforming their PFM systems. A contrasting expectation is that aid dependent countries invest less in such reforms relative to similar countries that rely more on domestic revenues, due to stronger accountability relationships in the latter and negative effects of aid dependence on the coherence of the public sector (Brautigam and Knack 2004 and Moss et al. 2006). Thus, the exploration here is whether any clear cross-country pattern, either positive or negative, is statistically significant. To test for potential measurement error of ODA and to check our results, we substitute aid with both Country Programmable Assistance (which excludes volatile aid such as debt relief and emergency relief as well as donor overhead cost which is spent outside of the recipient country) and Technical Cooperation (see Table A3.1, columns 4 and 5). Finally, we check for inclusion and completion of the HIPC process, to explore whether this group of countries differs significantly in terms of PFM performance from others.

A first macro-political driver that we test is _political stability._ Political stability is widely considered a necessary ingredient for developing and improving institutions; and as mentioned in section 2, earlier work by de Renzio et al. (2011) has confirmed the opposite, i.e. fragility, to

> 23 See Baunsgaard, Villafuerte, Poplawski-Riberio, and Richmond (2012), “Fiscal Frameworks for Resource Rich Developing Countries,” International Monetary Fund.

> 24 Royalties are excluded; while company income tax paid by resource-related companies are included. 25 We cross-checked and verified the consistency of the data with the OECD database.

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