Cheap talk and costly consequences
Name
1142235692-MIT.pdf
Size
2.77 MB
Format
Adobe PDF
Checksum (MD5)
7422d08b8b13e997a0886665d141d706
Author(s)
Loaiza Saa, Isabella.
Advisor(s)
Alex ('Sandy') Pentland.
Date Issued
2019
Publisher
Massachusetts Institute of Technology
Abstract
In this thesis, we use data on political interactions between country pairs to predict changes in trade. We implemented and applied a new feature selection algorithm called Boruta to build a compact set of predictor variables for this task. After finding a consistent set of features we used a Random Forest Classifier to predict bilateral changes in trade between 1998-2014. To better understand the contribution of each of the predictor variables used in the model we employ three different methods for calculating feature importance. Our results suggest that political and diplomatic interaction at at least as important (if not more) as distance and for predicting changes in trade.
Description
Thesis: S.M., Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, 2019
Cataloged from PDF version of thesis.
Includes bibliographical references (pages 39-41).
Subjects
Program in Media Arts and Sciences
MIT Department
Program in Media Arts and Sciences (Massachusetts Institute of Technology)
Terms of Use
MIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission.
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