Posted by: admin 1 month, 3 weeks ago

(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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