**4. Results**

The eco-efficiency MPI for the G18 in the BAU scenario shows the highest average value in 2000 (1.020) and lowest value in 2010 (0.973) (Table 3). The drop in the average value of the MPI between 2000 and 2010 was likely due to the global financial crisis (2008– 2009). The G18 mean value recovers after 2010 and records a value of 1.00 in 2040. Table 3 presents country-specific geometric mean values for the complete sample period (1997 to 2040) as well as two sub-periods. Calculations for the first sub-period (1997 to 2019) use the actual data to calculate MPI. Calculations for the second sub-period (2019 to 2040) use the forecasted values to calculate MPI. For the G18 countries, the average annual change in

MPI over the period 1997 to 2019 was 0.5%, while the forecasted average annual change over the period 2019 to 2040 was a 0.1% decrease. Over the complete sample (1997 to 2040), the average annual change in MPI was 0.2%. For the G18 countries, there has been little change in eco-efficiency.

**Table 3.** Eco-efficiency MPI for the BAU scenario.


Geometric mean computed for the periods 1997 to 2019, 2019 to 2040, and 1997 to 2040 denoted by geom1, geom2, and geom3, respectively. Rank refers to the ranking of the geomean.

Over the period 1997 to 2019, countries that recorded geometric mean values of MPI greater than unity include Argentina, Australia, Brazil, Germany, France, Great Britain, Italy, Japan, Mexico, Russia, Turkey, and the USA. France, Great Britain, and Russia record the three highest geometric mean values. Canada, China, India, Indonesia, Korea, and South Africa recorded negative average growth over this time period. Notice that the ranking of geometric mean values does not separate clearly on country income grouping. Russia, an emerging economy, has a high geometric mean value, while Canada, a developed G7 country, has a low value. The results change slightly over the second sub-period 2019 to 2040, as most countries experience lower MPI growth. One of the biggest differences is that South Korea now has a geometric mean value greater than one. For the period 1997 to 2040, Argentina, Australia, Germany, France, Great Britain, Italy, Japan, Mexico, Russia, and the United States each have improved their MPI. Over the period 1997 to 2040, the highest MPI growth is observed for Great Britain, France, and Russia, while the lowest growth is observed for Canada, China, India, Indonesia, Turkey, and South Africa. Notice that China and India, the two largest countries in the world by population, are experiencing a decline in MPI over the time period 1997 to 2040.

The G18 average catch-up value is highest in 2010 and lowest in 2040 (Table 4). The G18 experienced an increase in catch-up over the periods 1997–2019 and 1997–2040. The average catch-up effect is positive over the period 1997 to 2019 but negative over the period 2019 to 2040.


**Table 4.** Eco-efficiency catch-up for the BAU scenario.

Geometric mean computed for the periods 1997 to 2019, 2019 to 2040, and 1997 to 2040 denoted by geom1, geom2, and geom3, respectively. Rank refers to the ranking of the geomean.

Countries that have an increase in catch-up over all three sub-periods include Australia, Germany, Japan, Korea, and Russia. In other words, only five of the 18 countries studied improved their eco-efficiency catch-up over all three sub-periods.

The G18 average frontier-shift value is highest in 2020 and 2040 and lowest in 2010 (Table 5). As a group, the G18 recorded an increase in frontier-shift in the 2019 to 2040 sub-period but not in the 1997 to 2019 or 1997 to 2040 periods. Countries that showed an increase in frontier-shift growth over the period 2019 to 2040 are Brazil, Germany, France, Great Britain, Italy, Russia, Turkey, and the United States. Eight out of eighteen countries report an increase in frontier-shift over the period 2019 to 2040.

**Table 5.** Eco-efficiency frontier shift for the BAU scenario.


Geometric mean computed for the period 1997 to 2019, 2019 to 2040, and 1997 to 2040 denoted by geom1, geom2, and geom3 respectively. Rank refers to the ranking of the geometric mean.
