Scope of the analysis is to detect the most important factors that influence the decision-making process for the Official Development Assistance allocation. Several econometric models were implemented to deeply study the issue, each one considering different types of explanatory variables: the first model used the typical variables that traditionally enter a gravity model (GDP per capita of the recipient and distance between the donor and the recipient); in the second, institutional and cultural variables were selected; finally, in the third, the focus was on mere economic features. The data reveal that a specific set of variables is much more statistically significant in explaining the allocation decision, while others do not add any valuable information to the model. Also, two clear biases emerge: a proximity bias towards countries geographically closer and a small country bias, showing that countries with limited population tend to receive a bigger amount of ODA.
Lo scopo della ricerca è identificare i principali fattori che influenzano la decisione di dove indirizzare gli Aiuti pubblici allo sviluppo da parte dei Paesi donatori. Per fare questo, tre modelli econometrici sono stati sviluppati, ciascuno prendendo in considerazione diversi aspetti: nel primo, le variabili tradizionali del modello gravitazionale sono state considerate (PIL pro capite dei Paesi riceventi e distanza); nel secondo, alcune variabili istituzionali e culturale; nel terzo, aspetti prettamente economici. I dati mostrano che alcune variabili sono decisamente più significative di altre nello spiegare come vengono assegnati gli Aiuti allo Sviluppo, mentre emergono anche alcune inclinazioni, come la preferenza per Paesi riceventi più vicini geograficamente o per Paesi con popolazioni più ridotte.
An econometric analysis on the allocation of Official Development Assistance
FABRIS, SIMONA
2018/2019
Abstract
Scope of the analysis is to detect the most important factors that influence the decision-making process for the Official Development Assistance allocation. Several econometric models were implemented to deeply study the issue, each one considering different types of explanatory variables: the first model used the typical variables that traditionally enter a gravity model (GDP per capita of the recipient and distance between the donor and the recipient); in the second, institutional and cultural variables were selected; finally, in the third, the focus was on mere economic features. The data reveal that a specific set of variables is much more statistically significant in explaining the allocation decision, while others do not add any valuable information to the model. Also, two clear biases emerge: a proximity bias towards countries geographically closer and a small country bias, showing that countries with limited population tend to receive a bigger amount of ODA.È consentito all'utente scaricare e condividere i documenti disponibili a testo pieno in UNITESI UNIPV nel rispetto della licenza Creative Commons del tipo CC BY NC ND.
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https://hdl.handle.net/20.500.14239/8231