How to create output gap with Python and Anaconda

(Comments)

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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