## _5. Conclusion_

Another example showcasing the SDG network method compares the number of SDGs in which countries are succesful to their density. Mexico and Bolivia are successful with about the same number of SDG indicators included in this study: 282 in Mexico and 271 in Bolivia. Despite this, Mexico’s density is significantly higher than for Bolivia. This means Mexico’s successes are located in a more dense part of the SDG network, i.e., Mexico is doing well in those SDGs that have a high potential to make the development of other SDGs successful. The implication is that it would be easier for Mexico than for Bolivia to take advantage of its opportunities.

Imagine there is a global or regional SDG problem, or an organization dealing with local problems in several countries, then priorities between countries is on the table. Table 6 shows the example of the SDG indicator “access to electricity”, with the corresponding densities for three African countries that are currently underperforming for their income per capita levels. All else equal, investing in Rwanda would entail a higher probability of success since the country is successful in more of the SDGs in the proximity of “access to electricity”. Compared to the other countries with a lower density for this particular SDG, Rwanda has an underlying capacity that is more in line with what is needed for improvement of “access to electricity”.

Table 6: sample of country densities for “Access to electricity, % of population”

|Country|Densityfor Access to electricity|
|---|---|
|Rwanda|0.641|
|Uganda|0.594|
|Tanzania|0.499|

Source: Authors’ calculations

# 5. Conclusion

The UN 2030 Agenda and the Sustainable Development Goals (SDG), adopted by the world’s leaders in September 2015, ire comprehensive and holistic in nature, as they includes 17 goals and 169 targets covering economic, social, and environmental dimensions of development (UN 2015). The ambitious agenda articulates that no one shall be left behind, and that all shall collectively benefit from the fruits of development across all the SDGs. Individual countries now face the tough challenge of translating this agenda into feasible and realistic, yet ambitious, development plans as well as identifying policies that comprehensively reflect their initial conditions and priorities. This study builds on the idea that the SDGs are both products of countries’ current capacities, and a contributor to future capacities. Hence there is an element of path dependency, which needs to be taken into account as countries prioritize their SDG policies.

The SDG network is based on the same idea as the product space developed by Hausmann and Klinger (2006) and Hildalgo et al (2007), and combines it with the insights from the Country Development Diagnostics Post‐2015 framework (Gable et el, 2015). SDG achievements mirror the underlying structures that possess and combine available input in the country (the underlying capacities). The ease with which an input can be moved between two SDGs depends on their degree of commonality, conceptualized in the proximity between them. Proximity is the conditional probability of two SDG indicators being “successful” together. Successful is defined as a country performing better than expected, or as expected, _for its income per capita level_ . Centrality is the _sum_ of an SDG’s pair‐wise proximities with all other SDG indicators. As such, it is a measure of potential diversity and contribution to success of the overall SDG agenda in the country.

Not surprisingly, different measures of access to electricity are among the most connected SDGs, therefore implying that if a country has successfully provided access to electricity, it is likely that success will ensue in other SDGs as well. As indicated by the pair‐wise correlation matrix in Table A.1 in the annex, the groups of SDGs that exhibit 14