When Ying Gao arrived in São Paulo to research Brazil’s booming soybean sector, she did not expect the analysis to lead back to her native China; but when it did, it also renewed her career passion.
Ying Gao, here at Ibirapuera Park, spent a summer researching Brazilian regional economy in Sao Paulo.

Data

In Brazil’s leading urban and regional economics lab at the University of São Paulo, MIT graduate student Ying Gao used the lab’s statistical data to develop a new regional input-output economic model to analyze the country’s soybean sector.  Right away, she discovered that exports to her native China was driving the sector’s recent growth in Brazil.  “I had some expectations about it, but to see the numbers clearly was really surprising.”

She sifted through hundreds of industry data by applying regional economic theories and statistical software.  First, she focused on key sectors that supported or depended on soybean production.  Then she picked eight key soy producing states in Brazil, so that she could look at a network of different industries in diverse Brazilian regions that actually made up the Brazilian soybean industry.  She also investigated environmental implications related to how soybeans were being transported in those regions.

Collaboration

Her Brazilian colleagues at the lab helped her throughout the process by giving her lectures about Brazilian economy over many cups of coffee, explaining the statistical data in Portuguese, and providing feedback when modeling seemed to run into roadblocks.  The results were surprising to both, showing that while all states were affected by China-bound growth, local economic and environmental costs and benefits could vary because of how the soybean sector was organized differently among regions within Brazil.

Results

Following up on her work, Ying and her research group are working on a paper to publish the results.  After her summer research internship in São Paulo, Ying felt that the experience was invaluable because of the excellent quality of original data that would not have been available at MIT.  Moreover, applying economic theory and modeling techniques she learned at MIT in a developing country gave her challenges as well as opportunities in solving those issues by collaborating with international colleagues.  “It definitively confirmed my passion for regional economic development policy.  I think that because we are so connected in global economy, it’s all the more important to sift through those complexities to try to understand local impacts when making decisions about development, together.”  A perspective that she has gained and feels will help her whenever she works internationally in her career.  

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