Factors Influencing ICLEI Membership

What makes an ICLEI member city?

ICLEI – Local Governments for Sustainability, is an international NGO who works with local institutions, primarily municipalities, to support the implementation of sustainable goals.  One of the primary mechanisms that ICLEI uses to implement its programs is through official membership, for which they charge a small yearly fee.  In return, members gain access to grant opportunities, international recognition, publications, workshops, and opportunities to participate in sustainability programs.  The ICLEI website lists 1173 local governments and associated entities as current members, representing 81 countries.  947 of these members are local municipalities (cities, towns, etc.) and the other 226 are city networks, nonprofits, and county or regional governments. With the ICLEI membership being so vital to ICLEI as an organization, and often serving as a primary support vehicle for the implementation of the UN’s Agenda 21, this analysis seeks to determine whether there are correlative properties that serve as country-level indicators for city membership in ICLEI.

Methodology

My analysis utilizes the list of members available here on ICLEI’s website.  I then separated cities, villages, towns, and other small governments from regional or county level governments, networks, NGOs and other such groups.  As a rough indicator of the level of participation of cities in each country, I used the number of city members divided by country population, resulting in numbers from just over 3 per million citizens to zero.  Zero indicates countries that did not have small government members, but only had regional or other types of members instead (see figure below).  The two top scoring countries, the Maldives and Iceland, each have relatively small populations and contain one city that is a member and that also accounts for about a third of their total populations.  Subsequent countries have less extreme ratios of member cities to total population.

I then looked at 4 potential country-level indicators for city membership, including (1) the presence of an ICLEI regional office in the country, (2) Kyoto protocol signatories, (3) GDP per capita, and (4) the GINI index (a common measure of equity defined by the World Bank).  I will explain here why I selected each variable.

(1) The ICLEI website indicates regional offices in South Africa, Canada, the United States, Germany, Japan, Korea, Brazil, Mexico, Australia, India, and the Philippines.  These 11 countries account for 850 memberships – nearly 75% of total memberships (529 of these are in the U.S.)  I hypothesized that having a regional office in country would correlate with higher membership rates due to stronger ICLEI networks in countries with ICLEI staff.  (source: http://www.iclei.org/index.php?id=global-contact-us)

(2) I used signing the Kyoto protocol as a rough indicator of how environmentally mindful the national government was in a particular country (see somewhat out-of-date map below to get an idea).  I did not take into account ratification status, since nearly every country in this analysis has ratified other than Canada and the U.S.  This variable could result in a higher likelihood of membership due to the environmental leanings of the national government being a reflection of the views of citizenry.  Alternatively, however, it is possible that local governments in countries that had not signed the Kyoto protocol would need the use ICLEI’s services more, due to lack of national government support.  This would generate a negative correlation between the two variables.  Either way, I expected this variable to have some effect on membership rates. (source: http://en.wikipedia.org/wiki/List_of_parties_to_the_Kyoto_Protocol)

(3) GDP per capita serves as a measure of country wealth, and often as an indicator of citizen interest in environmental measures, especially due to the impression that sustainable activities reduce economic prosperity.  I expected GDP to correlate positively with membership. (source: http://data.worldbank.org/indicator/NY.GDP.PCAP.CD/countries)

(4) The GINI index measures the disparity between the wealthiest and the poorest in a country.  This can be used as another type of measurement for country prosperity, and I expected it to correlate positively with membership. (source: http://data.worldbank.org/indicator/SI.POV.GINI)

In plain English, I expected that member cities would be more likely in countries that contained a regional ICLEI office, had higher GDP, and higher income equality.  I wasn’t sure whether being Kyoto signatories would encourage or decrease membership rates, but expected there to be some effect.  I did not expect these indicators to correlate to a high degree with membership due to the complexities inherent in making the decision to join ICLEI, but expected to find some predictably of results.

World Map of Kyoto signatories and ratification status. 
Many more countries have since ratified the treaty, including Australia, Turkey, and over 20 others.
(photo source: morriscourse.com)

For the sake of simplicity, I used country-level information, since there were only 81 countries but over 900 cities.  Further investigations could look at city-level indicators in order to find potential greater correlation values and could take into account other variables such as municipality size or budget.

For the actual analysis, I utilized the freeware R, and performed a multiple linear regression on the data.

Results

After performing the multiple linear regression analysis, which uses the computer to perform calculus on the four variables to determine if any of them correlate with ICLEI membership, I found that the most correlative descriptor was GDP/capita.  Even this was not a big predictor, and could account only for a 1.32% increase in memberships per million people for each US$1,000 increase in GDP/capita.  Surprisingly, hosting an ICLEI office and the GINI index were not statistically significant factors.  I ended up dropping the GINI index from the analysis altogether since it was not helping overall accuracy of the results (read: R-squared values decreased).  Signing the Kyoto protocol had a slight negative correlation, but not one significant enough to account for much.

For those who prefer to read the statistics, here are the base results given by R:

Residuals:

     Min                 1Q         Median            3Q             Max

-0.82992    -0.40870    -0.15950     0.08209    2.66220

Coefficients:

                                           Estimate        Std. Error        t value        Pr(>|t|)   

(y-Intercept)                  4.047e-01      1.404e-01         2.882        0.00512

ICLEI office                     2.597e-02      2.373e-01         0.109        0.91315

Kyoto Signatory          -3.164e-01      1.646e-01       -1.922        0.05833

GDP/capita (US$1)      1.326e-05      3.846e-06         3.448        0.00092

Residual standard error: 0.7257 on 77 degrees of freedom

Multiple R-squared: 0.1597

Adjusted R-squared: 0.127

F-statistic: 4.879 on 3 and 77 DF

p-value: 0.003694

In an effort to find stronger correlations, I tried using all memberships rather than just cities, and various variables transformations.  None of these manipulations resulted in any headway on answering the question at hand.

Conclusions

I was so sure that hosting an ICLEI office would have a positive correlation with memberships that I would caution using these results without further analysis.  Purely looking at membership numbers would suggest such a trend, but it may be that higher GDP is in fact a stronger correlation.  These findings suggest that ICLEI memberships are more difficult to predict than I had originally anticipated.  This indicates that while it may be easier to gain memberships in wealthier countries, this is not a strong correlation, and is much weaker than might have been realized.  Thus far, it does not appear that there is a shortcut that can aid in gaining memberships more quickly.  This may also indicate that the globe is indeed pulling together, at least in cities, to work on global issues, and is not as divided as the Kyoto protocol or income inequalities might indicate.

Future analyses may want to pursue energy sources or climate impact as possible drivers for membership as well.  Please send me your comments on what other options could be explored, or to request the raw data.