Master Thesis: Measuring Tradeflow Resilience

Project Dates: May 2021 - September 2021

This project was submitted as my second year master thesis at Toulouse School of Economics, under external supervision from Ralph Ossa, Chairman of the Economics Department at University of Zurich.

Project Overview

For my master thesis I developed a framework that allows for measuring trade flow resilience. I started by operationalizing the notion of resilience and showed that it entails two dimensions: recovery and reorientation. I then outlined how both dimensions can be parametrized in a smooth transition autoregressive model, a type of time series model. To guide practical application of the novel measure I tested its properties in a simulation framework and noted possible caveats. Lastly, I measured the resilience of German car exports and US electronics imports and found that cultural proximity between countries correlates positively with resilient trade.

Data Sources

The data for the Monte Carlo simulation is based on 3 simulated data generating processes. The data for the empirical application comes from UN Comtrade monthly database.

Tools Used

The paper was built using LaTex. The coding was done in R and Matlab, using the tsDyn and forecast package as well as geospatial packages for visualizations. Code is available upon request.