For EPP grading, while the stata codes and the paper contains group works, all the .py and .ipynb files and more than half of the stata codes are written by myself.

This respiratory stores project for the course Research Module in Applied Microeconomics, the project topic is: Are Foreign Aid Contributions Associated with Population-Level Altruism?

This paper studies whether governmental humanitarian aid contributions are correlated with the altruistic preference in the population and if democratic systems reinforce this association. Based on a globally representative survey on preference, we estimate the relationship between altruism, democracy, and foreign aid which is expected by the political-economic theory proposed by Chong/Gradstein (2008), using a modified static panel data model. The full result could be read in paper.pdf.

mybinder is also a possible viewing option. To ensure the reproductivity, this project is connected to Travis. Dataset used in the project is zipped as data.zip. auxilary.py stores function that is used across ipython notebooks. environment request is specified in env.yml.

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Data_management :

Formatting

containing stata do file that is used to generate tables and graphs in the report, this folder is cooperatively contributed by the team.

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Cleaning.ipynb :

Data processing step 1

Merging the data that is needed for our research project, using countries as the key, variable explanations could be viewed here.

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Wide_to_long.ipynb :

Data processing step 2

Transform data from wide to long and setting up variables to suit the data preference of stata.

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Panel.ipynb :

Final model fitting

Applying FEF model in Pesaran, M. Hashem; Zhou, Qiankun (2014) : Estimation of Time-invariant Effects in Static Panel Data Models to estimate the effect of time-invariant variables, altruism in the panel data.

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Imputation.ipynb :

Model improvement

In this notebook, 3 different types of imputations are applied to deal with the problem of missing values in Gini index that is brought up in panel.ipynb.

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Timeseries_check.ipynb :

Data exploring

This notebook is created during attempts to fit models and explore data. Checking the time correlation by plotting and tests.

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EDA.ipynb :

Data exploring

This notebook is created during exploring data. EDA stands for primarily exploratory data analysis. Containing plots of relationship between different sets of variables by years.

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Gmmiv.ipynb :

Data exploring

This notebook is created during attempts to fit models. An attempt to apply OLS, 2SLS and GMM models in package linearmodels on the data set.

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