# **5. Benchmarking: Which Policies Would Bring Ethiopia the Biggest Bang for the Birr?**

We address this question by simulating alternative values for the explanatory variables in the model – one by one. Specifically, we benchmark Ethiopia against Sub-Saharan African (SSA) and lower-middle-income (LMIC) peers. We use the 90th percentile of best-performing SSA countries (in each of the respective variables), and the 75th percentile of best-performing lowermiddle-income countries. These benchmark values are depicted in Table 3. LMICs have a real GDP per capita between US$981 and 4,526 (PPP) in the Late 2000s period in our data set, compared to US$599 in Ethiopia. We note that these benchmarks are ambitious, but they are chosen to better highlight the effects of benchmarking.

Despite recent progress on some fronts, Ethiopia still lags behind on various aspects that are important for growth. For example, while our analysis shows that infrastructure improvements have been important for economic growth, this does not mean that Ethiopia’s infrastructure level does not lag behind and would not require further improvements. Quite the contrary, as shown in Table 3, the gap in infrastructure between Ethiopia and benchmark countries from Sub-Saharan Africa and with lower-middle-income status is still very substantial. The same is true for secondary education, inflation, and financial intermediation. Compared to the median of lowmiddle-income countries and the best performers of SSA, Ethiopia also underperforms on institutions.

**_-_** **_<u>Table 1: Benchmarking Structural, Stabilization and External Factors (2006 10 data).</u>_**

|**Variable**|**Ethiopia**|**Lowe**|**r Middle In**|**come Count**|**ries**|**SSA**|
|---|---|---|---|---|---|---|
|||**25%**|**Median**|**Average **|**75%**|**90%**|
|Real GDP per capita (PPP), US$|599.3|1,443.3|2,257.4|2,247.3|3,575.6|7,389.2|
|Real Exchange Rate|39.7|40.0|47.7|49.2|60.2|40.7|
|Secondary enrolment (gross, %)|32.8|42.2|55.0|54.9|82.1|86.0|
|Private sector credit (% of GDP)|20.1|14.1|25.9|23.6|36.7|44.5|
|Trade openness|0.2|-0.2|0.1|0.1|0.3|0.4|
|Gov. consumption (% of GDP)|9.1|7.9|11.0|12.3|19.5|6.4|
|CPI Inflation (annual, %)|18.4|6.0|8.8|8.7|12.0|4.3|
|Telephone Lines (per person)|1.1|1.3|4.0|3.4|8.8|7.0|
|Mobile phones (subscriptions)|3.7|30.0|44.5|40.0|57.1|78.0|
|Roads|0.5|1.6|2.9|2.6|4.1|6.2|
|Banking crisis (0=no; 1=yes)|0|0|0|0|0|0|
|Polity2(governance variable)|12.0|8.0|14.5|11.1|19.0|19.0|

Note that the best performing country depends on the variable in question. The 75<sup>th</sup> percentile is generally the ‘best performer’ for LMICs, however, for some variables that have a negative impact on growth it is the 25<sup>th</sup> percentile (exchange rate, government consumption, banking crisis and inflation). To facilitate interpretation we have underlined the relevant benchmark. Source: Authors’ calculation based on main data set.

The most important gaps to close are not necessarily the largest ones, but the ones that matter the most for raising the growth rate. As our econometric model implies, some reforms will have a higher impact on growth than others. Our goal is thus to identify those gaps which will bring 22