Descripción de Variables

Librerias necesarias para correr análisis

library(lmtest)
library(PerformanceAnalytics)

Creación de variables

v1po_cre_chi=(c(10.63587106,9.550832179,7.863736449,7.766150098,7.425763656,7.041328879,6.848762205,6.947200793,6.749773832,5.949714233,2.3))
v2crepp_chi=(c(10.10283262,9.027174425,7.339468994,7.23540947,6.883229179,6.498792133,6.271762691,6.350904743,6.26420964,5.571840828,1.979188895))
v3balcom_chi=(c(3.653587778,2.395474104,2.717522082,2.454133296,2.11490586,3.24399043,2.27434509,1.752140736,0.7679635,1.155372341,2.486934641))
v4gasto_chi=(c(14.58702058,15.23886494,15.75607839,15.88401589,15.81704465,16.21788677,16.36375556,16.32486222,16.53580834,16.77051095,16.8))
v5cuentacor_chi=(c(3.906751888,1.802248021,2.524448448,1.54856488,2.253281048,2.649016055,1.703305668,1.532655174,0.173668413,0.720660551,1.860934648))
v6desempleo_chi=(c(4.5,4.5,4.6,4.6,4.6,4.6,4.5,4.4,4.3,4.6,5))
v7inf_chi=(c(6.881380253,8.075684467,2.331217576,2.163370027,1.031063688,-0.002944094,1.407346027,4.232681975,3.499747636,1.287452077,0.671929892))
v8tasint_chi=(c(-1.002401214,-1.402428747,3.585203529,3.755387055,4.522308432,4.353072252,2.901815389,0.112553973,0.821501872,3.023620261,3.653521008))
v9gini_chi=(c(48.1,47.7,47.4,47.3,46.9,46.2,46.5,46.7,46.8,46.5,47.0))
v10edu_chi=(c(3.65,3.9,4.25,4.1,4.1,4.2,4.16,4.14,4.1,4.04,4.03))
v11id_chi=(c(1.71371996,1.78033996,1.91214001,1.99785995,2.02242994,2.05700994,2.10033011,2.11602998,2.14057994,2.2446301,2.40092993))
v12ied_e_chi=(c(4.0035629,3.708828902,2.827090556,3.039875469,2.559233447,2.192181603,1.55564215,1.349132679,1.693905294,1.310718778,1.723183793))
v13ied_s_chi=(c(0.952062415,0.641205592,0.761388132,0.762463765,1.175384509,1.576547892,1.926636988,1.123380739,1.029351959,0.958757698,1.046597368))
v14fbk_chi=(c(46.5561547,46.6601211,46.2252656,46.39894934,45.82395276,43.23480666,42.63137693,43.01329739,43.79347517,43.25110564,43.36667433))
v15fbk_cre_chi=(c(15.87935008,8.826938372,7.502720386,9.368834224,7.472976215,3.560256259,7.239269861,6.323959396,6.75917008,3.98596553,4.310804079))

Creación de las series de tiempo de las variables.

v1ts_po_cre_chi=ts(v1po_cre_chi,start=2010)
v2ts_crepp_chi=ts(v2crepp_chi,start=2010)
v3ts_balcom_chi=ts(v3balcom_chi,start=2010)
v4ts_gasto_chi=ts(v4gasto_chi,start=2010)
v5ts_cuentacor_chi=ts(v5cuentacor_chi,start=2010)
v6ts_desempleo_chi=ts(v6desempleo_chi,start=2010)
v7ts_inf_chi=ts(v7inf_chi,start=2010)
v8ts_tasint_chi=ts(v8tasint_chi,start=2010)
v9ts_gini_chi=ts(v9gini_chi,start=2010)
v10ts_edu_chi=ts(v10edu_chi,start=2010)
v11ts_id_chi=ts(v11id_chi,start=2010)
v12ts_ied_e_chi=ts(v12ied_e_chi,start=2010)
v13ts_ied_s_chi=ts(v13ied_s_chi,start=2010)
v14ts_fbk_chi=ts(v14fbk_chi,start=2010)
v15ts_fbk_cre_chi=ts(v15fbk_cre_chi,start=2010)

Creación de logaritmos de las series de tiempo.

v1lts_po_cre_chi=log(v1ts_po_cre_chi)
v2lts_crepp_chi=log(v2ts_crepp_chi)
v3lts_balcom_chi=log(v3ts_balcom_chi)
v4lts_gasto_chi=log(v4ts_gasto_chi)
v5lts_cuentacor_chi=log(v5ts_cuentacor_chi)
v6lts_desempleo_chi=log(v6ts_desempleo_chi)
v7lts_inf_chi=log(abs(v7ts_inf_chi))
v8lts_tasint_chi=log(abs(v8ts_tasint_chi))#tiene negativos
v9lts_gini_chi=log(v9ts_gini_chi)
v10lts_edu_chi=log(v10ts_edu_chi)
v11lts_id_chi=log(v11ts_id_chi)
v12lts_ied_e_chi=log(v12ts_ied_e_chi)
v13lts_ied_s_chi=log(v13ts_ied_s_chi)
v14lts_fbk_chi=log(v14ts_fbk_chi)
v15lts_fbk_cre_chi=log(v15ts_fbk_cre_chi)

Creación de la tabla.

t1chi_2010_2020=data.frame(v1po_cre_chi,v2crepp_chi,v3balcom_chi,v4gasto_chi,v5cuentacor_chi,v6desempleo_chi,v7inf_chi,v8tasint_chi,v9gini_chi,v10edu_chi,v11id_chi,v12ied_e_chi,v13ied_s_chi,v14fbk_chi,v15fbk_cre_chi)

Análisis de relaciones concatenadas.

plot(t1chi_2010_2020)

Gráficos de densidad y dispersión

library(ggplot2)
library(GGally)

Set 1

var1=data.frame(v1lts_po_cre_chi,v2lts_crepp_chi,v4lts_gasto_chi,v9lts_gini_chi,v11lts_id_chi,v12lts_ied_e_chi)
ggpairs(var1,          # Data frame
        columns = 1:6) # Columnas 

Set 2

var2=data.frame(v2lts_crepp_chi,v4lts_gasto_chi,v9lts_gini_chi,v11lts_id_chi,v3lts_balcom_chi,v12lts_ied_e_chi)
ggpairs(var2,          # Data frame
        columns = 1:6) # Columnas

Set 3

var3=data.frame(v3lts_balcom_chi,v5lts_cuentacor_chi)
ggpairs(var3,          # Data frame
        columns = 1:2) # Columnas

Set 4

var4=data.frame(v11lts_id_chi,v12lts_ied_e_chi)
ggpairs(var4,          # Data frame
        columns = 1:2) # Columnas

Set 5

var5=data.frame(v4lts_gasto_chi,v11lts_id_chi,v12lts_ied_e_chi,v14lts_fbk_chi)
ggpairs(var5,          # Data frame
        columns = 1:4) # Columnas

Set 6

var6=data.frame(v5lts_cuentacor_chi,v12lts_ied_e_chi)
ggpairs(var6,          # Data frame
        columns = 1:2) # Columnas

Set 7

var7=data.frame(v9lts_gini_chi,v11lts_id_chi)
ggpairs(var7,          # Data frame
        columns = 1:2) # Columnas

Este análisis forma parte del artículo The Determinants of China`s Inequality in the 21st Century realizado por los doctores Edgar Samid Limón Villegas, Juan González García y Jorge Ignacio Villaseñor Becerra.