121 PREDICTING MARKETS IN TIMES OF DISASTER: THESIS AUKE TAS

Master’s thesis: ‘Predicting the state of local markets after natural disasters to inform humanitarian cash programs 

WHAT IS IT ABOUT

Cash based aid empowers the affected population to decide how to meet their own needs using available local resources. In order to access these resources, there must be an accessible and well-supplied local market. The master’s thesis investigates the market functioning after a disaster.  

WHO IS THE AUTHOR

Auke Tas is finishing his master’s studies in Econometrics and Management Science, specialization Quantitative Marketing and Business Analytics. He has a bachelor’s degree in Econometrics from the Erasmus University Rotterdam 

WHY IS IT NEEDED

One of the conditions for cash based aid to be effective is the proper functioning of the local markets in the affected areas. Without it, the population cannot use the received cash to buy the commodities they need. At the same time, the disaster itself may have a negative impact on the marketplace.  

A prediction of the state of local markets after a disaster can help humanitarian organization provide aid more effectively. Knowing how well a market is functioning informs the decision of whether cash aid is an appropriate response.  

HOW WE WORKED TOGETHER

510 is developing the cash based aid product 121and our knowledge has informed Auke’s research, particularly in the areas of cash transfers and market functioning. Auke was supervised by a 510 team member who helped him focus the research in terms of region, timeframe and disaster types. 

WHAT THE MAIN FINDINGS ARE

The research indicated three factors that have a positive effect on the proper functioning of markets after disasters. Firstly, countries more exposed to natural hazards tend to better adapt to keep functioning after disasters. Secondly and thirdly, the institutional and infrastructural coping capacity and, to a lesser extent, the vulnerability of a country were also found to positively impact market functioning.  

The models created in this research did not result in high accuracy predictions, most likely due to the quality of data available. The state of markets after a disaster is not systematically kept in track, particularly in the investigated Sub-Saharan Africa region.  

WHEN & WHERE WE STARTED

  • 2017: 121 started system design.  
  • 2018-2019: Co-design sessions for the 121 in St. Maarten, Ukraine, Malawi & Ethiopia. 
  • SEP 2019: Master’s thesis finalizedThe research used data from disasters in Ethiopia, Kenya & Malawi in the last 10 years.

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