Cheap talk and costly consequences
Author(s)Loaiza Saa, Isabella.
Program in Media Arts and Sciences (Massachusetts Institute of Technology)
Alex ('Sandy') Pentland.
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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.
Thesis: S.M., Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, 2019Cataloged from PDF version of thesis.Includes bibliographical references (pages 39-41).
DepartmentProgram in Media Arts and Sciences (Massachusetts Institute of Technology)
Massachusetts Institute of Technology
Program in Media Arts and Sciences