How to create output gap with Python and Anaconda
Posted by: admin 4 months, 3 weeks ago
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Outpugap is the difference between the real output with the trend
it can be built with any computer programming, from Matlab to Python
This time I will use Hamilton filter with Python
and the requirement the data has to be not adjusted based on season
here is the code
####################################
import pandas as pd
import statsmodels.api as sm
def hamilton_filter(data, lambda_value=1600):
"""
Hamilton filter to estimate the output gap.
Parameters:
- data: Pandas DataFrame with a column 'Y' representing the log of real GDP.
- lambda_value: Smoothing parameter (default is 1600).
Returns:
- Pandas DataFrame with additional columns 'trend' and 'output_gap'.
"""
# Ensure the input data is a DataFrame with a column 'Y'
if 'Y' not in data.columns:
raise ValueError("Input data must have a column 'Y' representing the log of real GDP.")
# Apply Hamilton filter
cycle, trend = sm.tsa.filters.hpfilter(data['Y'], lamb=lambda_value)
# Calculate the output gap
output_gap = data['Y'] - trend
# Create a new DataFrame with the results
result_df = pd.DataFrame({
'trend': trend,
'output_gap': output_gap
}, index=data.index)
return result_df
# Load data from 'outputgap_kr.xls'
input_file_path = 'outputgap_kr.xlsx'
df = pd.read_excel(input_file_path, sheet_name='Sheet1') # Assuming the sheet name is 'Sheet1'
# Apply Hamilton filter
output_gap_df = hamilton_filter(df)
# Save the result to 'outputgap_result_kr.xls'
output_file_path = 'outputgap_result_kr.xlsx'
output_gap_df.to_excel(output_file_path, sheet_name='OutputGapResult', index=True)
####################
and now you have to prepare the file in the name of outputgap_kr.xls and make sure you have column with header Y
the output basically made automatically!
Now enjoy your code
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