Setup

import numpy as np import pandas as pd import matplotlib.pyplot as plt import seaborn as sns import plotly.express as px import plotly.graph_objects as go #chart_studio.tools.set_credentials_file(username='econdata777', api_key='ADDhere') import statsmodels.api as sm import statsmodels.formula.api as smf import warnings #warnings.filterwarnings('ignore')

Import data

df1 = pd.read_csv("https://raw.githubusercontent.com/quarcs-lab/mendez2020-convergence-clubs-code-data/master/assets/dat.csv") #df1 = pd.read_csv("https://raw.githubusercontent.com/quarcs-lab/mendez2020-convergence-clubs-code-data/master/assets/dat.csv", parse_dates =['year'])

df1

idint64

1 - 108

countryobject

Albania0.9%

Algeria0.9%

106 others98.1%

Albania

Algeria

df1.columns

df1.dtypes

df1['country'].unique()

Dataset definitions

# Import definitions of dataset df1_def = pd.read_csv("https://raw.githubusercontent.com/quarcs-lab/mendez2020-convergence-clubs-code-data/master//assets/dat-definitions.csv") df1_def

var_nameobject

country3.6%

year3.6%

26 others92.9%

var_defobject

Standardized country name (from PWT)3.6%

Year3.6%

26 others92.9%

log_GDPpc

Trend (HP400) of log of GDP per capita

log_lp

Trend (HP400) of log of labor productivity

log_ky

Trend (HP400) of log of Capital-Output Ratio

log_h

Trend (HP400) of log of Human Capital

log_tfp

Trend (HP400) of log of Aggregate Efficiency

region

Regional group (Classification of the UN)

hi1990

High income country (as of 1990, World Bank classification)

isocode

ISO code from the PWT9.0

Descriptive statistics

df1.describe().round(2)

idfloat64

yearfloat64

count

2700

mean

54.5

2002

std

31.18

7.21

min

1990

25%

27.75

1996

50%

54.5

2002

75%

81.25

2008

max

108

2014

Select

df1.log_lp

df2 = df1[['country', 'year', 'log_lp', 's']] df2

countryobject

Albania0.9%

Algeria0.9%

106 others98.1%

yearint64

1990 - 2014

Albania

1990

Albania

1991

Albania

1992

Albania

1993

Albania

1994

Albania

1995

Albania

1996

Albania

1997

Albania

1998

Albania

1999

Query

df_2014 = df1[['country', 'region', 'hi1990', 'year', 'log_lp', 's']].query("year == 2014") df_2014

countryobject

Albania0.9%

Algeria0.9%

106 others98.1%

regionobject

Europe27.8%

Asia25.9%

3 others46.3%

Albania

Europe

Algeria

Africa

Argentina

Americas

Armenia

Asia

124

Australia

Oceania

149

Austria

Europe

174

Bangladesh

Asia

199

Belgium

Europe

224

Benin

Africa

249

Bolivia

Americas

df_vietnam = df1[