Proposed SNA (still a work in progress)- Can trade flows help determine the level of happiness/ innovation in a country?

Goal of the research

To identify quantitative and qualitative differences in trade flows of countries in the dataset and determine whether they are a predictor of where a country would lie on the happiness/ innovation scale.

Dataset

Innovative countries (list below)

Happy Countries (list below)

Their top 5 trading partners

	Innovative Countries Bloomberg Innovation Index http://www.bloomberg.com/slideshow/2013-02-01/50-most-innovative-countries.html#slide51	Happy Countries UN World Happiness Report  http://unsdsn.org/files/2013/09/WorldHappinessReport2013_online.pdf
1	US	Denmark
2	South Korea	Norway
3	Germany	Switzerland
4	Finland	Netherlands
5	Sweden	Sweden
6	Japan	Canada
7	Singapore	Finland
8	Austria	Austria
9	Denmark	Iceland
10	France	Australia

Data

BACI-CEPII database which contains international trade data on 178 countries and 5,000 products.

Methodology

- Determine Eigenvector centralities for countries in the dataset based on their influence on world trade.

- Visualize the binary network and present some general characteristics

- Visualize the weighted network and determine in-degree and out-degree, eigenvector and closeness centralities for each node.

- Use the BACI-CEPII database to determine the composition of imports/ exports of each country and create attributes for each country based on the level of sophistication- basic/ intermediate/ hi value add. Visualize the network by using these attributes.

Limitations

- The small size of the dataset might limit the predictive value of the analysis.

- Other exogenous factors that influence a country’s level of innovation/ happiness have not been considered in this analysis.