Social Network Analysis and the Digital Evolution Index

Abstract:

Through Social Network Analysis, we will examine the relationships between countries. We would like to begin to take the Digital Evolution Index (DEI) to the next level by examining how countries interact in terms of flows of capital, exchange of information, trade, and investment. By examining relationships or ties between countries, we hope to further explore some of the conclusions drawn as a result of the the analysis.

I. Overview: Digital Evolution Index

• The DEI was introduced in September 2014 by the Fletcher School in conjunction with Mastercard. By examining demand conditions, supply conditions, the institutional environment and innovation, the index has ranked 50 countries globally by their drivers of “digital evolution” from 2008-2011. As a result of the ranking the countries were found to fall into one of four categories:
• Stall Outs
• Countries have achieved a high level of evolution in the past but are losing momentum and risk falling behind.
• Stand Outs
• Countries have shown high levels of digital development in the past and continue to remain on an upward trajectory.
• Break Outs
• Countries have the potential to develop strong digital economies. Though their overall score is still low, they are moving upward and are poised to become Stand Out countries in the future.
• Watch Outs
• Countries face significant opportunities and challenges, with low scores on both current level and upward motion of their DEI. Some may be able to overcome limitations with clever innovations and stopgap measures, while others seem to be stuck.
• Commercial Application
• Analyze strength of ties among countries in Break Out and Watch Out segments to look for correlations and relationships
• By examining the relationships between Break Out and Watch Out markets, we can provide data to companies with strategies to sell across national borders to markets with high levels of similarities
• Gaps
  

  • The DEI looked at country data, but did not look at cross country data to see how various countries are related
  • Lack of data on migration flows and aid flows restricted the ability for those factors to be included in the index

II. Project Plan

• Through Social Network Analysis, we will examine the relationships between countries. We would like to begin to take the DEI to the next level by examining how countries interact in terms of flows of capital, exchange of information, trade, and investment. By examining relationships or ties between countries, we hope to further explore some of the conclusions drawn as a result of the the analysis.
• Focus on idea of networks between countries, narrowing in on the idea of the neighborhood effect
• What explains outliers, what links:
• Stand outs
• Stall outs
• Break outs
• Watch outs
• By examining network relationships, further the research and provide recommendations for the next generation of the DEI.

III. Objectives, Research Questions, and SNA Methods

In order to broadly examine the networks, for each research objective, we will employ SNA methods with cross country data, outlined throughout the various attributes in the objectives noted below. Furthermore, we will broadly integrate attribute data gathered for use in the DEI for each of our research objectives:

• Developing vs. Developed
• A country is deemed to be developing or developed mainly on the basis of economics, per capita income, industrialization, literacy rate, living standards etc.  A developed country has a highly developed economy and advanced technological infrastructure relative to other less developed nations.
• Multilateral membership
• Multilateral membership consists of contributions made between one institution and a recipient institution that are made in favor of development. Multilateral institutions are those that are international agencies or organizations whose members are governments, or a fund managed autonomously by such an agency, and pools of contributions so that they lose their identity and become an integral part of its financial assets.
• Neighborhood
• Subsection of a larger community; a collection of both people and institutions occupying a spatially defined area influenced by ecological, cultural, and sometimes political forces where local communities do not form their identities only as the result of free-market competition. Instead, some communities have their identity and boundaries imposed on them by outsiders.
• Per Capita Gross Domestic product (GDP)
• A measure of the total output of a country that takes the GDP and divides it by the number of people in the country. The per capita GDP is especially useful when comparing one country to another because it shows the relative performance of the countries. A rise in per capita GDP signals growth in the economy and tends to translate as an increase in productivity.
• Total GDP
• Total GDP is the sum of gross value added by all resident producers in the economy plus any product taxes and minus any subsidies not included in the value of the products. It is calculated without making deductions for depreciation of fabricated assets or for depletion and degradation of natural resources.
• Population size
• Population size is the total membership or population or “universe” of a defined class of people, objects or events.

Objective 1: Neighborhood Effect - To conduct a network analysis to explore the social capital and quality of flows of capital, exchange of information, trade, and investment linkages between countries based upon their geographical location.

• Research Questions:
• Define the the neighborhood effect. Is it real, or is there something stronger that links the countries?
• What explains the outliers in the neighborhood effect?
• Why do ASEAN countries seem to have a stronger neighborhood effect?
• Are there any natural points of collusion among neighboring countries? The clustering around ASEAN and South East Asia begs the question of whether there is a natural network or is trade facilitated through a regional cooperation?
• SNA Methods: We will analyze whether centrality measures, including closeness, eigenvector, and betweenness, can be measured to make meaningful comparisons among various countries who are geographically close in proximity with one another and those that are not. We will use the analysis to investigate the link strength or weakness of a country’s multilateral membership based upon a two-mode, dichotomized dataset that will illustrate any links between countries and multilaterals.
• Attributes:
• The role that geographical proximity plays in the formation of linkages.
• Countries that are similar to one another on some characteristic more likely to form a connection.
• Trade Flows: One-mode dataset Description of Data from SNA
• Linkages by free trade agreements: Both one-mode and two-mode dichotomized dataset
• Memberships in any alliance, e.g., intergovernmental, effects on the likelihood of linkages forming among countries.
• Migration Flows: One-mode dataset (migration flows in and out of break out and watch out countries) (what is opposite of dichotomized?--likeness or similarity)

Objective 2: Focus on Break Outs - To conduct a network analysis of the level of investment spending, including aid flows, FDI transactions (including those transactions made by sovereign wealth funds), and sovereign debt ownership, to determine the growth or decline of investment shares of GDP.

• Research Questions:

• What links countries categorized as break outs?
• Drivers for the recommendations for China?
• SNA Methods: We will begin using centrality in two-mode networks as our initial data suggests that there are centrality scores for investment transactions across jurisdictions, with a clearly specified relationship between them. We will then use some form of betweenness centrality to study affiliation networks to determine whether less central, developing countries experience technological infrastructure advancements only when more central, developed countries are investing, and vice versa
• Attributes:  
• Aid Flows: One-mode dataset examining the flow of aid in and out of chosen countries
• Foreign Direct Investment (FDI) transactions (transactions made by sovereign wealth funds)
• Sovereign debt ownership
• Index tool that gauges level of economic exposure as a function of economies, with an emphasis on China

Objective 3: Focus on Watch Outs - To conduct a network analysis of how migration effects impact countries in our population experience both gains and losses in the short-term and whether such gains and losses change over the longer term.

• Research Questions:

• What links countries categorized as Watch Outs?
• Do these linkages serve as indicators for future growth in digital evolution?
• What makes India unique?
• Do the network connections provide any indications that may point to increased or decreased risk for investment in these countries.
• SNA Methods: We will assess the strength of ties between countries by reviewing the volume and value of remittances so that we can evaluate whether certain countries are more stable and predictable as compared to other financial flows. Our aim is to verify to what extent the existence of networks with major centrality contributes to favor the increase in the number of migrants. We want to test our belief that in cases of higher centrality, the information flows easily through the links and nodes of the network, but the center of the network is critical for the transmission of information.
• Attributes:  
• Remittance payment transactions between countries
• Internet traffic flows
• Commercial air traffic patterns: One-mode, dichotomized dataset