import wooldridge as woo
import pandas as pd
import statsmodels.api as sm
import statsmodels.formula.api as smf

phillips = woo.dataWoo('phillips')
T = len(phillips)

# define yearly time series beginning in 1948:
date_range = pd.date_range(start='1948', periods=T, freq='Y')
phillips.index = date_range.year

# estimation of both Phillips curve models:
yt96 = (phillips['year'] <= 1996)
phillips['inf_diff1'] = phillips['inf'].diff()
reg_s = smf.ols(formula='Q("inf") ~ unem', data=phillips, subset=yt96)
reg_ea = smf.ols(formula='inf_diff1 ~ unem', data=phillips, subset=yt96)
results_s = reg_s.fit()
results_ea = reg_ea.fit()

# DW tests:
DW_s = sm.stats.stattools.durbin_watson(results_s.resid)
DW_ea = sm.stats.stattools.durbin_watson(results_ea.resid)
print(f'DW_s: {DW_s}\n')
print(f'DW_ea: {DW_ea}\n')