TeIAS-PythonCourse/course_project_with_answers.py at master · einian85/TeIAS-PythonCourse · GitHub

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# -*- coding: utf-8 -*-
"""Course-Project-with-answers.ipynb

Automatically generated by Colaboratory.

Original file is located at
    https://colab.research.google.com/drive/1dLxE7pTTKF6jA-yl4wE3ftjnIN07Zmm_

# Summer 2022 Python for Econ Students Course Project
## Student Name
## نام دانشجو

## Read data
You have to read the data from an excel file.
The excel file can be found here:
https://dl.dropboxusercontent.com/s/xsywvv5p5p8k9kq/MB_Data.xlsx

variable:
MB: Monetary Base
MB_gr: Monetary Base Growth
Expansion: Dummy variabel that is 1 in expansion periods and 0 in recession periods
Recession: Dummy variabel that is 1 in recession periods and 0 in expansion periods
NonOilGDP: Real Non-oil GDP of Iran
NonOilGDPCycle: Deviations of NonOilGDP from it's trends
"""

import pandas as pd
import numpy as np

D = pd.read_excel("https://dl.dropboxusercontent.com/s/xsywvv5p5p8k9kq/MB_Data.xlsx")

"""## Preview data
Show a part of data
"""

D

"""## Slice data
Keep only rows that include data on Expansion and Recession

"""

D2 = D[D.Expansion.notna()]
D2

"""## Plot data
Plot time series data of monetary base growth.
Add additional background bars that show recession periods.
"""

import matplotlib.pyplot as plt
tm = (D2.Year + (D2.Quarter-1)/4).to_numpy()
rc = D2.Recession.to_numpy()
fig, ax = plt.subplots()
ax2 = ax.twinx()
ax.bar(tm,rc,color='lightgrey',width=.25)
ax.get_yaxis().set_visible(False)
ax2.plot(tm,D2.MB_gr)
fig.show()

"""plot the time series data for recession and expansion period in different colors"""

import matplotlib.pyplot as plt
tm = (D2.Year + (D2.Quarter-1)/4).to_numpy()
rc = D2.Recession.to_numpy()
fig, ax = plt.subplots()
ax2 = ax.twinx()
ax.bar(tm,rc,color='lightgrey',width=.25)
ax.get_yaxis().set_visible(False)
gx = D2.MB_gr.to_numpy().copy()
gr = D2.MB_gr.to_numpy().copy()
gx[rc==1]=np.nan
gr[rc==0]=np.nan
ax2.plot(tm,gx)
ax2.plot(tm,gr)
fig.show()

"""## Average Growth of monetary base
The given growth rate is quarterly growth rate
* Calculate and report the average quarterly growth rate
* Calculate and report the average annual growth rate _(note that it's not 4*quarterly rate!)_

"""

g=D2.MB_gr.to_numpy()
mean_q_g = np.mean(g)
mean_a_g = np.mean((g+1)**4-1)
mean_a_g_2 = mean_q_g * 4

print(mean_q_g)
print(mean_a_g)
print(mean_a_g_2)

"""## Calculate means in expansions and recessions

"""

ex = D2.Expansion.to_numpy()

mean_ex = np.mean(g[ex==1])
print(mean_ex)

mean_rc = np.mean(g[ex==0])
print(mean_rc)

"""## Test the equality of means of monetary base growth in recession and expansions """

import statsmodels.stats.weightstats as sms
import scipy.stats as scs

g_ex = g[ex==1]
g_rc = g[ex==0]

t1 = sms.ttest_ind(g_ex,g_rc)
t2 = scs.ttest_ind(g_ex,g_rc)

print(t1)
print(t2)

"""##Test the equality of variances of monetary base growth in recensiions and expansion """

F = g_rc.var()/g_ex.var()
print(F)

df1 = len(g_rc)-1
df2 = len(g_ex)-1

alpha = 0.05
p_value = scs.f.cdf(F,df1,df2)*2
print(p_value)