Growth and Development Class, Winter 2019, IDEA PhD, UAB.
Software used: Python To begin with, the codes are structured in a manner to make interpretation easier and to enhance reproducibility. The codes are structured as follows:
- For agricultural production, profit and crop production is titled 'agric'
- For consumption including livestock and others is titled 'csp'
- For labor wages, business profit and transfers is titled 'labor'
- For social demography / background/descriptive statistics of respondents is titled 'socdem'
- For merging of the above 1 - 4 dataset is titled 'fullanalysis'
- For the problem set 1 questions is titled 'PS1'
- For the fulldata without the labor information is titled 'fulldata.csv'
- The complete data with labor information such as hours per worker 'h' and ‘eh’ hours worked per adult in a household Note: The only difference between fulldata.csv and labordata.csv is that labordata.csv contains 'h' and 'eh'. Yeah, i may be stupid at times as i should have merged the them together, but i couldn't solve for 'h' and 'eh' for a while and i left out questions regarding it until i got it right.
- The results, output and intepretation of charts, tables and other comments of the problem set is titled 'BabaniyiOlaniyiFullUpdatedPS1'
- Functions for trimming is titled "data_functions_albert". Many thanks to Albert Rodriguez
Software used: Python
- The solution is titled 'BabaniyiGnDPS2'
- Python code is titled 'BabaniyiGnDPS2.py'
Software used: Python and R I used pythin for data imputation and cleansing, and R for iterating the regression and corresponding graphs.
- The solution is titled 'PS3BabaniyiOlaniyi'
- Python code is titled 'PS3.py'
- R code is titled 'PS3.R'
- Data used is titled 'dataUGA.dta'