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From Recognition to Adaptation: How does Forecasting relate to International Aid Funding in Food Security?

Grawehr, Matthias LU and Gunnarsson, Þórarinn LU (2019) VBRM15 20191
Division of Risk Management and Societal Safety
Abstract
The importance of early adaptation to reduce the impact of recognized risks has been underlined in recent years as featured aspect of the Sustainable Development Goals and the Sendai Framework for Action. The aim of this study is to analyze the relationship between forecasted food insecurity levels and allocated funding directed at food security. The dataset was built by combining quantitative data on food insecurity forecasts (FEWS NET), international aid funding addressing food insecurity (UN OCHA) and population distribution (NASA) as well as by the use of GIS analyzing tools. The statistical analysis of the dataset shows that there is a strong positive correlation between forecast and funding streams in the 27 analyzed countries over... (More)
The importance of early adaptation to reduce the impact of recognized risks has been underlined in recent years as featured aspect of the Sustainable Development Goals and the Sendai Framework for Action. The aim of this study is to analyze the relationship between forecasted food insecurity levels and allocated funding directed at food security. The dataset was built by combining quantitative data on food insecurity forecasts (FEWS NET), international aid funding addressing food insecurity (UN OCHA) and population distribution (NASA) as well as by the use of GIS analyzing tools. The statistical analysis of the dataset shows that there is a strong positive correlation between forecast and funding streams in the 27 analyzed countries over the analyzed period from 2011 and 2018. There has been an increase in the strength of this relationship from the year 2012, indicating a greater response to forecasts and learning to reduce the risk of food insecurity. Further, the analysis indicates that the country characteristics: population size (negative) and density (negative), the Human Development Index (negative), the year of independence (positive) as well as whether a country has an UNISDR National Platform (negative) weakly correlate to the funding per person per forecasted food insecurity level. The discussion reflects on the high complexity of the system and the potential for strengthening the relationship between recognition and adaptation for improving early warning systems, forecast-based early action and disaster risk reduction. (Less)
Popular Abstract
The relationship between forecasts of and funding to address food insecurity

The importance to act early to reduce potential dangers has been highlighted in several international guidelines in the last years. This study looks at the relationship between forecasted food insecurity levels and funding distributed to increase food security.

Data was collected about food insecurity forecasts, international aid funding directed towards food insecurity and population distribution. The data was analyzed with the use of tools for mapping and statistics. The study shows that there is a strong connection between forecast and funding streams in the studied area of 27 countries and in the study period from 2011 and 2018. Further, the study finds... (More)
The relationship between forecasts of and funding to address food insecurity

The importance to act early to reduce potential dangers has been highlighted in several international guidelines in the last years. This study looks at the relationship between forecasted food insecurity levels and funding distributed to increase food security.

Data was collected about food insecurity forecasts, international aid funding directed towards food insecurity and population distribution. The data was analyzed with the use of tools for mapping and statistics. The study shows that there is a strong connection between forecast and funding streams in the studied area of 27 countries and in the study period from 2011 and 2018. Further, the study finds an increase in the relationship from the year 2012 until 2018. This indicates that there is a better response to forecasts and action is taken earlier. The research also shows that the country characteristics: population size and density, the Human Development Index, the year of independence and whether a country has an UNISDR National Platform relate weakly to the funding for each person per forecasted food insecurity level. The discussion reveals the high complexity of the system, the potential for strengthening the relationship between recognition and adaptation and the hope of on-going improvements to act early to reduce the dangers of food insecurity. (Less)
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author
Grawehr, Matthias LU and Gunnarsson, Þórarinn LU
supervisor
organization
course
VBRM15 20191
year
type
H2 - Master's Degree (Two Years)
subject
keywords
Forecasting, Food Insecurity, Famine, Funding, FEWS NET, Disaster Risk Reduction, Early Warning System, Complexity, Recognition, Adaptation
language
English
id
8984270
date added to LUP
2019-06-20 08:35:57
date last changed
2019-06-20 08:35:57
@misc{8984270,
  abstract     = {The importance of early adaptation to reduce the impact of recognized risks has been underlined in recent years as featured aspect of the Sustainable Development Goals and the Sendai Framework for Action. The aim of this study is to analyze the relationship between forecasted food insecurity levels and allocated funding directed at food security. The dataset was built by combining quantitative data on food insecurity forecasts (FEWS NET), international aid funding addressing food insecurity (UN OCHA) and population distribution (NASA) as well as by the use of GIS analyzing tools. The statistical analysis of the dataset shows that there is a strong positive correlation between forecast and funding streams in the 27 analyzed countries over the analyzed period from 2011 and 2018. There has been an increase in the strength of this relationship from the year 2012, indicating a greater response to forecasts and learning to reduce the risk of food insecurity. Further, the analysis indicates that the country characteristics: population size (negative) and density (negative), the Human Development Index (negative), the year of independence (positive) as well as whether a country has an UNISDR National Platform (negative) weakly correlate to the funding per person per forecasted food insecurity level. The discussion reflects on the high complexity of the system and the potential for strengthening the relationship between recognition and adaptation for improving early warning systems, forecast-based early action and disaster risk reduction.},
  author       = {Grawehr, Matthias and Gunnarsson, Þórarinn},
  keyword      = {Forecasting,Food Insecurity,Famine,Funding,FEWS NET,Disaster Risk Reduction,Early Warning System,Complexity,Recognition,Adaptation},
  language     = {eng},
  note         = {Student Paper},
  title        = {From Recognition to Adaptation: How does Forecasting relate to International Aid Funding in Food Security?},
  year         = {2019},
}