When interpreting these results, two features of the performed DEA should be kept in mind. First, for any given country there are three possible factors behind an increase in DEA scores: an increase in the country’s revenue relative to its GDP, a decline in the DEA input index (corresponding to less favorable economic conditions), and changes in the frontier due to developments in other countries. As can be seen in Table 2, changes in the DEA input index were generally very small over this period. The improvements in efficiency can thus be attributed either to increases in revenues or to changes in the frontier.<sup>19</sup> The fact that there are several cases in Table 2 in which DEA scores increased despite declining revenues (as a percentage of GDP) suggests that changes in the frontier play a crucial role for the changes in DEA scores.

Moreover, when looking at changes in countries’ revenue mobilization performance across time, it is important to note that the frontier analysis is designed to track countries’ relative performance within the sample (i.e., in comparison to other countries during the same time period) rather than countries’ absolute performance over time. This means that the DEA scores (as well as the values of the input index) cannot be directly compared across time. Instead, similar scores in two periods indicate that the _relative_ performance of a country within the sample remained about the same. This approach has the advantage that it controls for general time effects, i.e., events that affect all countries simultaneously in a given period. For example, suppose country A achieves a score of 0.4 in the first period and 0.5 in the second period. It might be the case that revenues in fact declined from the first to the second period. This might be the case if a global shock (such as the Financial Crisis) negatively affected revenue mobilization in all countries, but country A managed to cope with the shock relatively better than other countries. In this case, country A would have improved its performance relative to the other countries in the sample despite a decline in its revenue-to-GDP ratio.

**Table 3.** Regression Results: Dependent Variable—DEA Efficiency Score

||(1)|(2)|(3)|(4)|(5)|(6)|(7)|(8)|(9)|(10)|
|---|---|---|---|---|---|---|---|---|---|---|
|Technological|0.074<sup>**</sup>||||||0.064<sup>***</sup>|0.138<sup>**</sup>|0.066<sup>***</sup>|0.045|
|readiness|(0.014)||||||(0.003)|(0.013)|(0.010)|(0.198)|
|Natural||0.003<sup>*</sup>|||||0.001|-0.005|-0.011|0.003|
|resources||(0.088)|||||(0.820)|(0.272)|(0.128)|(0.500)|
|Control of|||0.039<sup>*</sup>||||0.019|0.057|-0.018|-0.027|
|corruption|||(0.096)||||(0.733)|(0.496)|(0.833)|(0.770)|
|Tax policy||||0.068<sup>*</sup>||||0.017|||
|||||(0.066)||||(0.863)|||
|Informal|||||-0.003<sup>**</sup>||||0.006||
|sector|||||(0.014)||||(0.225)||
|Social trust||||||0.150||||0.079|
|||||||(0.387)||||(0.553)|
|Country FE|||||||yes|yes|yes|yes|
|Observations|240|345|354|213|126|84|237|127|111|78|
|Countries|86|116|118|75|70|46|85|49|59|42|
|R-squared|0.055|0.024|0.014|0.032|0.091|0.010|||||
|R-squ.(within)|||||||0.058|0.152|0.241|0.050|

_Notes:_ * p < 0.10, ** p < 0.05, *** p < 0.01. p-values in parentheses. Estimated via OLS. Standard errors are clustered at the country level. _Source:_ Authors’ analysis based on the variables and data sources described in Section III, Table 1.

> 19 Increases in revenues may stem from changes in tax policy and tax administration as well as from other factors (e.g., conflict, natural disasters, or commodity prices) which are not directly captured by the indicators included in the DEA input index.

18