Convergence of Digital Financial Inclusion in China's 31 Provinces
1. Introduction
2. Methodology & Data
2.1 Methodology
2.2 Data
2.3 Descriptive statistics
G.describe().round(3)
3. Exploratory data analysis
3.1 Data Visualization
px.line(
G,
x="year",
y="lnindex",
color="NAME_1"
)
px.line(G, x='year', y='lnindex', color='region', facet_col= 'part', facet_col_wrap= 2, height= 800)
px.box(
G,
x="lnindex",
color="part",
hover_name= 'NAME_1',
animation_frame = 'year'
)
gdf = gpd.read_file("/work/final.geojson")
gdf['gro']=gdf['lnindex2019']-gdf['lnindex2011']
gdf.describe().round(3)
4. Regression analysis
4.1 Absolute beta Convergence
px.scatter(
gdf,
x="lnindex2011",
y="gro",
color="part",
hover_name="region",
trendline="ols",
trendline_scope="overall"
)
px.scatter(
gdf,
x="lnindex2011",
y="gro",
color="part",
hover_name="region",
trendline="ols"
)
y = gdf['gro']
X = gdf['lnindex2011']
X_withconst = sm.add_constant(X)
OLS = sm.OLS(y, X_withconst).fit()
print(OLS.summary())
west=gdf.query('part=="West"')
y1 = west['gro']
X1 = west['lnindex2011']
X1_withconst = sm.add_constant(X1)
OLS1 = sm.OLS(y1, X1_withconst).fit()
print(OLS1.summary())
east=gdf.query('part=="East"')
y2 = east['gro']
X2 = east['lnindex2011']
X2_withconst = sm.add_constant(X2)
OLS2 = sm.OLS(y2, X2_withconst).fit()
print(OLS2.summary())
center=gdf.query('part=="Central"')
y3 = center['gro']
X3 = center['lnindex2011']
X3_withconst = sm.add_constant(X3)
OLS3 = sm.OLS(y3, X3_withconst).fit()
print(OLS3.summary())
4.2 Potential clusters
den = px.density_contour(
gdf,
x="lnindex2011",
y="gro"
)
den.update_traces(contours_coloring="fill", contours_showlabels = True, colorscale = 'peach')
den.show()
den = px.density_contour(
west,
x="lnindex2011",
y="gro",
)
den.update_traces(contours_coloring="fill", contours_showlabels = True, colorscale = 'peach')
den.show()
den = px.density_contour(
east,
x="lnindex2011",
y="gro",
)
den.update_traces(contours_coloring="fill", contours_showlabels = True, colorscale = 'peach')
den.show()
den = px.density_contour(
center,
x="lnindex2011",
y="gro",
)
den.update_traces(contours_coloring="fill", contours_showlabels = True, colorscale = 'peach')
den.show()
4.3 Conditional Convergence
smf.ols(formula='gro ~ lnindex2011+lnrgdp2011', data=gdf).fit().summary()