||expected negative effects of higher levels of<br>aid dependency (Brautigam and Knack 2004)<br>**Political/institution**<br>|**al variables**<br>||
|---|---|---|---|
|**Political**<br>**stability**|Greater political stability may facilitate<br>sustained improvements in institutions,<br>includingPFM systems|Worldwide<br>Governance<br>Indicators(WGI)|Political stability indicator<br>(rescaled: 1=least stable,<br>10=most stable)|
|**Regime**|In more democratic regimes, citizens are<br>expected to have more opportunities to hold<br>governments to account, creating an<br>incentive for politicians to seek PFM<br>improvements(de Renzio 2009)|Freedom House|Sum of Civil Liberties and<br>Political Rights Index (converted<br>to: 1=least democratic,<br>10=most democratic)|
|**Programmat**<br>**ic Parties**|Programmatic parties are expected to be able<br>to make credible commitments about<br>improving public service delivery; and as part<br>of this should have an incentive and<br>capabilities to improve PFM systems.|DPI, Beck et. al<br>2001 and Cruz &<br>Keefer, 2010|Fraction of parties in a country<br>that are programmatic (either<br>left, right, or center)|

Table A1.1 in the Annex summarizes the number of observations available for each of the presumed ‘driving’ variables for PFM performance, the minimum and maximum range actually observed for the variable as specified, and the means and standard deviations. As previously noted in section 3.1, we use a dataset of over 100 countries to study the cross-country relationship between PEFA scores and a variety of country characteristics. In the first-differences model, we look at within country variation over time for about 40 countries, given the much more limited number of countries for which at least two PEFA assessments are available.

Furthermore, table A2.1 shows the correlation statistics for these variables. Income is related to a number of the other variables used, including a negative relationship to the level of aid to GNI, and positively to tax revenue, the presence of programmatic parties, and political stability. There is also some correlation among the political variables as might be expected, in particular a positive relationship between regime type and the presence of programmatic parties.

# **4.3 Effects of PFM Quality**

The second relationship we examine is that between PFM quality and expected outcomes. As noted in section 2, this relationship is crucial from the perspective of the overall rationale for PFM reforms, but empirical work on this has been scant to date. Table 2 presents a summary of the left-hand-side variables that proxy fiscal performance along its three dimensions. The summary statistics of these variables are presented in Annex 1.

Following Vlaicu et al. (2014), our first outcome variable is the overall fiscal balance of a country, or _deficit,_ as a proxy for aggregate fiscal discipline _._ We use the general government primary net lending/borrowing as a percent of GDP according to the IMF’s World Economic Outlook database.<sup>29</sup> The variable is calculated as the three-year forward average beginning the year of

> 29 See: http://www.imf.org/external/pubs/ft/weo/2013/01/weodata/weoselgr.aspx.

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