Solucion del parcial 1

load("C:/Users/Eduardo/Downloads/BETO/Metodos 2020/importaciones_exportaciones/data_comercio_exterior_actualizacion.RData")
source('C:/Users/Eduardo/Downloads/funciones_comercio_exterior (1).R')

Ejercicio 1

Usando los datos de Comercio Exterior de El Salvador, disponibles en la base de datos preparada en clases, responda las siguientes preguntas:

Importante: muestre sus resultados en formato tabular, y asignando los encabezados y pies de página apropiados en cada caso

Clave 1

1- Calcule las exportaciones totales de El Salvador hacia la región de África Sub-Sahariana, para el periodo 2019-2020 son (en millones de US$)

library(dplyr)
library(kableExtra)

## Warning: package 'kableExtra' was built under R version 3.6.3

## 
## Attaching package: 'kableExtra'

## The following object is masked from 'package:dplyr':
## 
##     group_rows

data_comercio_exterior_actualizacion %>%
  select("anio","valor_fob","sub_region") %>% 
  filter(sub_region=="Africa Sub-Sahariana",anio %in% 2019:2020, valor_fob>0) %>%
  group_by(anio) %>%
  summarise(`Total de Exportaciones de El Salvador hacia África Sub-sahariana, millones US$`=sum(valor_fob)/1e6) %>% head() %>% 
  kable(caption="Exportaciones totales de El Salvador hacia África Sub-Sahariana, período 2019-2020") %>% kable_minimal() %>%
  add_footnote(label="Elaboración propia con base en datos del BCR",
               notation="symbol") %>% kable_styling()

## `summarise()` ungrouping output (override with `.groups` argument)

Exportaciones totales de El Salvador hacia África Sub-Sahariana, período 2019-2020

anio	Total de Exportaciones de El Salvador hacia África Sub-sahariana, millones US$
2019	2.452792
2020	1.503626
* Elaboración propia con base en datos del BCR

2- Obtenga el Saldo de la balanza comercial de El Salvador, con “Asia Sudoriental”, para el periodo 2017-2019, (en millones de US$)

library(dplyr)
library(kableExtra)
data_comercio_exterior_actualizacion %>%
  filter(cod_region=="142", anio %in% 2017:2019) %>%
  group_by(anio) %>%
  summarise(`Total Exportaciones a Asia Sudoriental MM US$`=sum(valor_fob)/1e6,
            `Total Importaciones de Asia Sudoriental MM US$`=sum(valor_cif)/1e6,
            `Balanza Comercial El Salvador-Asia Sudoriental MM $`=`Total Exportaciones a Asia Sudoriental MM US$`-`Total Importaciones de Asia Sudoriental MM US$`) %>% 
  head() %>% kable(caption = "Saldo  Balanza comercial El Salvador-Asia Sudoriental,2017-2019") %>% kable_minimal()  %>%  
  add_footnote(label="Elaboración propia con base en datos del BCR",
               notation="symbol") %>%  kable_styling()

## `summarise()` ungrouping output (override with `.groups` argument)

Saldo Balanza comercial El Salvador-Asia Sudoriental,2017-2019

anio	Total Exportaciones a Asia Sudoriental MM US$	Total Importaciones de Asia Sudoriental MM US$	Balanza Comercial El Salvador-Asia Sudoriental MM $
2017	215.3568	2541.096	-2325.739
2018	166.6960	2819.512	-2652.816
2019	132.9864	2812.391	-2679.405
* Elaboración propia con base en datos del BCR

3- Por cada dólar exportado a la región Sudamericana, en el año 2019, ¿Cuánto se importo?

data_comercio_exterior_actualizacion %>% filter(valor_cif==0, valor_fob>0, anio==2019,region_intermedia=="Sudamerica") %>% 
  summarise(`Total de exportaciones de ESA a Sudamérica`=sum(valor_fob))->exportaciones

data_comercio_exterior_actualizacion %>%
filter(region_intermedia=="Sudamerica", valor_cif>0, valor_fob==0, anio==2019) %>% 
  summarise(`Ratio de importaciones/exportaciones de ESA a Sudamérica`=sum(valor_cif))->importaciones

ratio_importaciones_exportaciones<- (importaciones/exportaciones)
print(ratio_importaciones_exportaciones)  %>% 
  head() %>% kable(caption = "Ratio importaciones/exportaciones de ESA-Sudamerica") %>% kable_minimal() %>% 
  add_footnote(label="Elaboración propia con base en datos del BCR",
               notation="symbol") %>%  kable_styling()

##   Ratio de importaciones/exportaciones de ESA a Sudamérica
## 1                                                 19.13248

Ratio importaciones/exportaciones de ESA-Sudamerica

Ratio de importaciones/exportaciones de ESA a Sudamérica
19.13248
* Elaboración propia con base en datos del BCR

4- Calcule el indicador de Balassa de El Salvador, con México, Estados Unidos y Canadá, durante el periodo 2017-2020, para el capitulo “01” del SAC.

capitulo<-"01"
data.frame("años"=2017:2020,
 "IB USA"=sapply(X = 2017:2020,
       FUN = indicadores_Balassa_capitulo,codigo_pais=840,capitulo="01"), 
      "IB Cánada"=sapply(X = 2017:2020,
       FUN = indicadores_Balassa_capitulo,codigo_pais=124,capitulo="01"), 
      "IB México"=sapply(X = 2017:2020,
       FUN = indicadores_Balassa_capitulo,codigo_pais=484,capitulo="01"))%>%
  

  head() %>% kable(caption = "Índice de Balassa de El Salvador, con México, Estados Unidos y Canadá para los años 2017-2020", digits = 4) %>% kable_minimal() %>% 
  add_footnote(label="Elaboración propia con base en datos del BCR",
               notation="symbol") %>%  kable_styling()

Índice de Balassa de El Salvador, con México, Estados Unidos y Canadá para los años 2017-2020

años	IB.USA	IB.Cánada	IB.México
2017	0.3598	0.3954	-0.5761
2018	0.3229	0.6144	-0.8244
2019	0.4016	0.1885	-0.8981
2020	0.7035	0.0411	-0.9775
* Elaboración propia con base en datos del BCR

Clave 2

1- Calcule el indicador de IVCR de El Salvador, con México, Estados Unidos y Canadá, durante el periodo 2017-2020, para el capitulo “01” del SAC.

library(kableExtra)
library(dplyr)
capitulo<-"01"
data.frame("años"=2017:2020,
      "IVCR USA"=sapply(X = 2017:2020,
       FUN = indicadores_IVCR_partida,codigo_pais=840,capitulo==capitulo), 
      "IVCR Cánada"=sapply(X = 2017:2020,
       FUN = indicadores_IVCR_partida,codigo_pais=124,capitulo==capitulo), 
      "IVCR México"=sapply(X = 2017:2020,
       FUN = indicadores_IVCR_partida,codigo_pais=484,capitulo==capitulo))%>%
  
head() %>% kable(caption = "Índice IVCR de El Salvador, con México, Estados Unidos y Canadá para los años 2017-2020") %>% kable_minimal() %>% 
  add_footnote(label="Elaboración propia con base en datos del BCR",
               notation="symbol") %>%  kable_styling()

Índice IVCR de El Salvador, con México, Estados Unidos y Canadá para los años 2017-2020

años	IVCR.USA	IVCR.Cánada	IVCR.México
2017	NaN	NaN	NaN
2018	NaN	NaN	NaN
2019	NaN	NaN	NaN
2020	NaN	NaN	NaN
* Elaboración propia con base en datos del BCR

capitulo<-"01"
data.frame("años"=2017:2020,
"IVCR_Mexico"=sapply(X=2017:2020,FUN = indicadores_IVCR_capitulo,codigo_pais=484,capitulo=capitulo),

"IVCR_USA"=sapply(X=2017:2020,FUN=indicadores_IVCR_capitulo,codigo_pais=840,capitulo=capitulo),
                                 
"IVCR_Canada"=sapply(X=2017:2020,FUN = indicadores_IVCR_capitulo,codigo_pais=124,capitulo=capitulo))%>%
  
head() %>% kable(caption = "Índice IVCR de El Salvador, con México, Estados Unidos y Canadá para los años 2017-2020") %>% kable_minimal() %>% 
  add_footnote(label="Elaboración propia con base en datos del BCR",
               notation="symbol") %>%  kable_styling()

Índice IVCR de El Salvador, con México, Estados Unidos y Canadá para los años 2017-2020

años	IVCR_Mexico	IVCR_USA	IVCR_Canada
2017	-0.0006366	-0.1268112	0.0025811
2018	-0.0047801	-0.0997253	0.0000473
2019	-0.0014925	-0.0880920	0.0003483
2020	-0.0013685	-0.0841604	-0.0027953
* Elaboración propia con base en datos del BCR

2- Por cada dólar exportado a la región Centroamericana , en el periodo 2017-2019, ¿Cuánto se importo? (resultado por año)

data_comercio_exterior_actualizacion %>% filter(valor_cif==0, valor_fob>0, anio==2017,region_intermedia=="Centroamérica") %>% 
  summarise(`Total de exportaciones de ESA a Centroamérica 2017`=sum(valor_fob))->exportaciones_1

data_comercio_exterior_actualizacion %>%
filter(region_intermedia=="Centroamérica", valor_cif>0, valor_fob==0, anio==2017) %>% 
  summarise(`Total de importaciones de ESA a Centroamérica 2017`=sum(valor_cif))->importaciones_1

ratio_importaciones_exportaciones_1<- (importaciones_1/exportaciones_1)
print(ratio_importaciones_exportaciones_1)  %>% 
  head() %>% kable(caption = "Ratio importaciones/exportaciones de ESA-Centroamérica durante 2017") %>% kable_minimal() %>% 
  add_footnote(label="Elaboración propia con base en datos del BCR",
               notation="symbol") %>%  kable_styling()

##   Total de importaciones de ESA a Centroamérica 2017
## 1                                           1.580565

Ratio importaciones/exportaciones de ESA-Centroamérica durante 2017

Total de importaciones de ESA a Centroamérica 2017
1.580565
* Elaboración propia con base en datos del BCR

data_comercio_exterior_actualizacion %>% filter(valor_cif==0, valor_fob>0, anio==2018,region_intermedia=="Centroamérica") %>% 
  summarise(`Total de exportaciones de ESA a Centroamérica 2018`=sum(valor_fob))->exportaciones_1

data_comercio_exterior_actualizacion %>%
filter(region_intermedia=="Centroamérica", valor_cif>0, valor_fob==0, anio==2018) %>% 
  summarise(`Total de importaciones de ESA a Centroamérica 2018`=sum(valor_cif))->importaciones_1

ratio_importaciones_exportaciones_1<- (importaciones_1/exportaciones_1)
print(ratio_importaciones_exportaciones_1)  %>% 
  head() %>% kable(caption = "Ratio importaciones/exportaciones de ESA-Centroamérica durante 2018") %>% kable_minimal() %>% 
  add_footnote(label="Elaboración propia con base en datos del BCR",
               notation="symbol") %>%  kable_styling()

##   Total de importaciones de ESA a Centroamérica 2018
## 1                                           1.743028

Ratio importaciones/exportaciones de ESA-Centroamérica durante 2018

Total de importaciones de ESA a Centroamérica 2018
1.743028
* Elaboración propia con base en datos del BCR

data_comercio_exterior_actualizacion %>% filter(valor_cif==0, valor_fob>0, anio==2019,region_intermedia=="Centroamérica") %>% 
  summarise(`Total de exportaciones de ESA a Centroamérica 2019`=sum(valor_fob))->exportaciones_1

data_comercio_exterior_actualizacion %>%
filter(region_intermedia=="Centroamérica", valor_cif>0, valor_fob==0, anio==2019) %>% 
  summarise(`Total de importaciones de ESA a Centroamérica 2019`=sum(valor_cif))->importaciones_1

ratio_importaciones_exportaciones_1<- (importaciones_1/exportaciones_1)
print(ratio_importaciones_exportaciones_1)  %>% 
  head() %>% kable(caption = "Ratio importaciones/exportaciones de ESA-Centroamérica durante 2019") %>% kable_minimal() %>% 
  add_footnote(label="Elaboración propia con base en datos del BCR",
               notation="symbol") %>%  kable_styling()

##   Total de importaciones de ESA a Centroamérica 2019
## 1                                           1.729294

Ratio importaciones/exportaciones de ESA-Centroamérica durante 2019

Total de importaciones de ESA a Centroamérica 2019
1.729294
* Elaboración propia con base en datos del BCR

3- Obtenga el Saldo de la balanza comercial de El Salvador, con el “Caribe”, para el periodo 2017-2019, (en millones de US$)

data_comercio_exterior_actualizacion %>%
  filter(region_intermedia=="Caribe",anio %in% 2017:2019) %>%
  group_by(anio) %>%
  summarise(`Total Exportaciones al Caribe  MM US$`=sum(valor_fob)/1e6,
            `Total Importaciones al Caribe MM US$`=sum(valor_cif)/1e6,
            `Balanza Comercial ESA-El Caribe MM $`=`Total Exportaciones al Caribe  MM US$`-`Total Importaciones al Caribe MM US$`) %>% 
  head() %>% kable(caption = "Saldo de la Balanza comercial de El Salvador-Caribe periodo 2017-2019") %>% kable_minimal()  %>% 
  add_footnote(label="Elaboración propia con base en datos del BCR",
               notation="symbol") %>%  kable_styling()

## `summarise()` ungrouping output (override with `.groups` argument)

Saldo de la Balanza comercial de El Salvador-Caribe periodo 2017-2019

anio	Total Exportaciones al Caribe MM US$	Total Importaciones al Caribe MM US$	Balanza Comercial ESA-El Caribe MM $
2017	150.1824	46.04799	104.1345
2018	172.1331	34.04536	138.0877
2019	169.1371	21.61247	147.5247
* Elaboración propia con base en datos del BCR

4- Calcule las exportaciones totales de El Salvador hacia la región Norte De Europa, para el periodo 2019-2020 son (en millones de US$)

library(dplyr)
library(kableExtra)
data_comercio_exterior_actualizacion %>%
  select("anio","valor_fob","sub_region") %>%
  filter(sub_region=="Norte De Europa",anio %in% 2019:2020,valor_fob>0) %>%
  group_by(anio) %>%
  summarise(`Total Exportaciones El Salvador al Norte De Europa MM US$`=sum(valor_fob)/1e6) %>% 
  head() %>% kable(caption = "Exportaciones totales de El Salvador hacia al Norte De Europa 2019-2020") %>% kable_minimal()  %>% 
  add_footnote(label="Elaboración propia con base en datos del BCR",
               notation="symbol") %>%  kable_styling()

## `summarise()` ungrouping output (override with `.groups` argument)

Exportaciones totales de El Salvador hacia al Norte De Europa 2019-2020

anio	Total Exportaciones El Salvador al Norte De Europa MM US$
2019	19.80854
2020	12.15218
* Elaboración propia con base en datos del BCR

Clave 3

1- Por cada dólar exportado a la región Suramericana, en el periodo 2018-2019, ¿Cuánto se importo? (resultado por año)

library(dplyr)
library(kableExtra)
data_comercio_exterior_actualizacion %>% filter(valor_cif==0, valor_fob>0, anio==2018,region_intermedia=="Sudamerica") %>% 
  summarise(`Total de exportaciones de ESA a Sudamerica 2018`=sum(valor_fob))->exportaciones_sudamerica_2018

data_comercio_exterior_actualizacion %>%
filter(region_intermedia=="Sudamerica", valor_cif>0, valor_fob==0, anio==2018) %>% 
  summarise(`Total de importaciones de ESA a Sudamerica 2018`=sum(valor_cif))->importaciones_sudamerica_2018

ratio_importaciones_exportaciones_sudamerica_2018<- (importaciones_sudamerica_2018/exportaciones_sudamerica_2018)
print(ratio_importaciones_exportaciones_sudamerica_2018)  %>% 
  head() %>% kable(caption = "Ratio importaciones/exportaciones de El Salvador-Suramerica durante 2018") %>% kable_minimal() %>% 
  add_footnote(label="Elaboración propia con base en datos del BCR",
               notation="symbol") %>%  kable_styling()

##   Total de importaciones de ESA a Sudamerica 2018
## 1                                        16.76119

Ratio importaciones/exportaciones de El Salvador-Suramerica durante 2018

Total de importaciones de ESA a Sudamerica 2018
16.76119
* Elaboración propia con base en datos del BCR

library(dplyr)
library(kableExtra)
data_comercio_exterior_actualizacion %>% filter(valor_cif==0, valor_fob>0, anio==2019,region_intermedia=="Sudamerica") %>% 
  summarise(`Total de exportaciones de ESA a Sudamerica 2019`=sum(valor_fob))->exportaciones_sudamerica_2019

data_comercio_exterior_actualizacion %>%
filter(region_intermedia=="Sudamerica", valor_cif>0, valor_fob==0, anio==2019) %>% 
  summarise(`Total de importaciones de ESA a Sudamerica 2019`=sum(valor_cif))->importaciones_sudamerica_2019

ratio_importaciones_exportaciones_sudamerica_2019<- (importaciones_sudamerica_2019/exportaciones_sudamerica_2019)
print(ratio_importaciones_exportaciones_sudamerica_2019)  %>% 
  head() %>% kable(caption = "Ratio importaciones/exportaciones de El Salvador-Suramerica durante 2019") %>% kable_minimal() %>% 
  add_footnote(label="Elaboración propia con base en datos del BCR",
               notation="symbol") %>%  kable_styling()

##   Total de importaciones de ESA a Sudamerica 2019
## 1                                        19.13248

Ratio importaciones/exportaciones de El Salvador-Suramerica durante 2019

Total de importaciones de ESA a Sudamerica 2019
19.13248
* Elaboración propia con base en datos del BCR

2- Calcule el IHH de El Salvador, con México, Estados Unidos y Canadá, durante el periodo 2017-2020, normalizado.

library(kableExtra)
library(dplyr)
data.frame("años"=2017:2020,
      "IHH USA"=sapply(X = 2017:2020,
       FUN = indicadores_IHH_Herfindahl_Hirschmann_anual,codigo_pais=840,normalizado=TRUE), 
      "IHH Cánada"=sapply(X = 2017:2020,
       FUN = indicadores_IHH_Herfindahl_Hirschmann_anual,codigo_pais=124,normalizado=TRUE), 
      "IHH México"=sapply(X = 2017:2020,
       FUN = indicadores_IHH_Herfindahl_Hirschmann_anual,codigo_pais=484,normalizado=TRUE))%>%
  
 head() %>% kable(caption = "Índice IHH normalizado de El Salvador, con México, Estados Unidos y Canadá para los años 2017-2020") %>% kable_minimal() %>% 
  add_footnote(label="Elaboración propia con base en datos del BCR",
               notation="symbol") %>%  kable_styling()

Índice IHH normalizado de El Salvador, con México, Estados Unidos y Canadá para los años 2017-2020

años	IHH.USA	IHH.Cánada	IHH.México
2017	0.0055910	0.1231022	0.0165526
2018	0.0056610	0.0084443	0.0182162
2019	0.0058727	0.1190248	0.0142813
2020	0.0098672	0.0590948	0.0146978
* Elaboración propia con base en datos del BCR

3- Calcule las exportaciones totales de El Salvador hacia la región de África Oriental, para el periodo 2017-2020 son (en millones de US$)

data_comercio_exterior_actualizacion %>%
  select("anio","valor_fob","region_intermedia") %>%
  filter(region_intermedia=="África Oriental",anio %in% 2017:2020,valor_fob>0) %>%
  group_by(anio) %>%
  summarise(`Total Exportaciones El Salvador a África Oriental MM US$`=sum(valor_fob)/1e6) %>% 
  head() %>% kable(caption = "Exportaciones totales de El Salvador a África Oriental periodo 2017-2020") %>% kable_minimal()  %>% 
  add_footnote(label="Elaboración propia con base en datos del BCR",
               notation="symbol") %>%  kable_styling()

## `summarise()` ungrouping output (override with `.groups` argument)

Exportaciones totales de El Salvador a África Oriental periodo 2017-2020

anio	Total Exportaciones El Salvador a África Oriental MM US$
2017	0.6734228
2018	4.0123130
2019	0.8439266
2020	0.0007570
* Elaboración propia con base en datos del BCR

4- Obtenga el Saldo de la balanza comercial de El Salvador, con Latinoamérica, para el periodo 2017-2019, (en millones de US$)

library(dplyr)
library(kableExtra)
data_comercio_exterior_actualizacion %>%
  filter(sub_region=="América Latina Y El Caribe",anio %in% 2017:2019) %>%
  group_by(anio) %>%
  summarise(`Total Exportaciones a América Latina y El Caribe MM US$`=sum(valor_fob)/1e6,
            `Total Importaciones a América Latina y El Caribe MM US$`=sum(valor_cif)/1e6,
            `Balanza Comercial ESA-América Latina y El Caribe MM $`=`Total Exportaciones a América Latina y El Caribe MM US$`-`Total Importaciones a América Latina y El Caribe MM US$`) %>% 
  head() %>% kable(caption = "Saldo de la Balanza comercial de El Salvador-América Latina y El Caribe durante el periodo 2017-2019") %>% kable_minimal()  %>% 
  add_footnote(label="Elaboración propia con base en datos del BCR",
               notation="symbol") %>%  kable_styling()

## `summarise()` ungrouping output (override with `.groups` argument)

Saldo de la Balanza comercial de El Salvador-América Latina y El Caribe durante el periodo 2017-2019

anio	Total Exportaciones a América Latina y El Caribe MM US$	Total Importaciones a América Latina y El Caribe MM US$	Balanza Comercial ESA-América Latina y El Caribe MM $
2017	2746.262	3770.895	-1024.633
2018	2922.872	4144.131	-1221.259
2019	3067.961	4553.745	-1485.784
* Elaboración propia con base en datos del BCR

Ejercicio 2

Usando los datos de la Penn World Table, de la Universidad de Groningen.

Resuelva los siguientes requerimientos (es importante mostrar todos sus resultados en formato tabular):

Clave 1

1- Construya una función que le permita elegir el país y filtrar para un periodo(inicio,final), muestre su uso filtrando los datos para El Salvador, en el periodo de 1950-2014.

library(pwt9)
data("pwt9.0")
funcion_filtro_pais_c1<- function(country,anio_inicio,anio_final) {
  pwt9.0 %>% filter(country==!!country,
                    year>=anio_inicio,
                    year<=anio_final) -> pais_periodo_1
  pais_periodo_1
}
funcion_filtro_pais_c1(country="El Salvador",anio_inicio=1950,anio_final=2014) %>%
 kable(caption = "Datos de El Salvador 1990-2014",
 digits = 1,align = "l") %>%
 kable_styling(bootstrap_options = "striped",
 full_width = TRUE)

Datos de El Salvador 1990-2014

	country	isocode	year	currency	rgdpe	rgdpo	pop	emp	avh	hc	ccon	cda	cgdpe	cgdpo	ck	ctfp	cwtfp	rgdpna	rconna	rdana	rkna	rtfpna	rwtfpna	labsh	delta	xr	pl_con	pl_da	pl_gdpo	i_cig	i_xm	i_xr	i_outlier	cor_exp	statcap	csh_c	csh_i	csh_g	csh_x	csh_m	csh_r	pl_c	pl_i	pl_g	pl_x	pl_m	pl_k
SLV-1950	El Salvador	SLV	1950	US Dollar	1328.7	1163.0	2.0	NA	NA	1.2	1106.2	1178.1	1276.2	1136.4	1489.4	NA	NA	6510.5	6671.5	6988.9	14268.6	NA	NA	NA	0.0	1	0.1	0.1	0.1	extrapolated	extrapolated	market	no	NA	NA	0.9	0.1	0.1	0.2	-0.3	0	0.1	0.1	0.1	0.1	0.1	0.2
SLV-1951	El Salvador	SLV	1951	US Dollar	1406.2	1163.4	2.0	NA	NA	1.2	1178.9	1267.0	1349.9	1105.5	1544.8	NA	NA	6766.9	7134.1	7564.4	14326.2	NA	NA	NA	0.0	1	0.1	0.1	0.1	extrapolated	extrapolated	market	no	NA	NA	0.9	0.1	0.1	0.2	-0.4	0	0.1	0.2	0.1	0.1	0.1	0.2
SLV-1952	El Salvador	SLV	1952	US Dollar	1488.1	1253.5	2.1	NA	NA	1.2	1251.2	1349.3	1420.9	1192.8	1588.6	NA	NA	7264.3	7644.2	8094.0	14409.0	NA	NA	NA	0.0	1	0.1	0.1	0.1	extrapolated	extrapolated	market	no	NA	NA	0.9	0.1	0.1	0.2	-0.4	0	0.1	0.2	0.1	0.1	0.1	0.2
SLV-1953	El Salvador	SLV	1953	US Dollar	1593.6	1346.1	2.1	NA	NA	1.2	1362.8	1464.0	1525.1	1305.6	1600.3	NA	NA	7817.6	8292.7	8739.8	14508.4	NA	NA	NA	0.0	1	0.1	0.1	0.1	extrapolated	extrapolated	market	no	NA	NA	0.9	0.1	0.1	0.2	-0.3	0	0.1	0.2	0.1	0.1	0.1	0.2
SLV-1954	El Salvador	SLV	1954	US Dollar	1690.6	1356.9	2.2	NA	NA	1.2	1451.0	1549.4	1615.6	1317.6	1580.2	NA	NA	8021.8	8827.7	9217.7	14583.3	NA	NA	NA	0.0	1	0.1	0.1	0.1	extrapolated	extrapolated	market	no	NA	NA	1.0	0.1	0.1	0.2	-0.4	0	0.1	0.2	0.1	0.2	0.1	0.2
SLV-1955	El Salvador	SLV	1955	US Dollar	1753.4	1425.7	2.3	NA	NA	1.2	1517.9	1618.2	1669.6	1384.1	1582.7	NA	NA	8445.0	9284.1	9673.2	14673.4	NA	NA	NA	0.0	1	0.1	0.1	0.1	extrapolated	extrapolated	market	no	NA	NA	1.0	0.1	0.1	0.2	-0.4	0	0.1	0.2	0.1	0.1	0.1	0.2
SLV-1956	El Salvador	SLV	1956	US Dollar	1828.7	1514.2	2.3	NA	NA	1.3	1564.4	1707.0	1730.1	1459.7	1657.9	NA	NA	8990.8	9644.4	10412.6	15037.8	NA	NA	NA	0.0	1	0.1	0.1	0.1	extrapolated	extrapolated	market	no	NA	NA	0.9	0.1	0.1	0.2	-0.4	0	0.1	0.2	0.1	0.1	0.1	0.2
SLV-1957	El Salvador	SLV	1957	US Dollar	1975.5	1593.0	2.4	NA	NA	1.3	1624.6	1784.3	1864.7	1527.8	1710.4	NA	NA	9393.5	10034.3	10928.6	15464.8	NA	NA	NA	0.0	1	0.1	0.1	0.1	extrapolated	extrapolated	market	no	NA	NA	0.9	0.1	0.1	0.2	-0.4	0	0.1	0.2	0.1	0.2	0.1	0.2
SLV-1958	El Salvador	SLV	1958	US Dollar	1892.2	1650.9	2.5	NA	NA	1.3	1628.0	1763.6	1785.9	1607.5	1703.7	NA	NA	9519.5	10066.1	10701.7	15672.7	NA	NA	NA	0.0	1	0.1	0.1	0.1	extrapolated	extrapolated	market	no	NA	NA	0.9	0.1	0.1	0.2	-0.3	0	0.1	0.2	0.1	0.1	0.1	0.2
SLV-1959	El Salvador	SLV	1959	US Dollar	1908.1	1710.7	2.5	NA	NA	1.3	1668.1	1771.1	1790.0	1664.5	1698.6	NA	NA	9704.6	10381.5	10665.8	15646.0	NA	NA	NA	0.0	1	0.1	0.1	0.1	extrapolated	extrapolated	market	no	NA	NA	0.9	0.1	0.1	0.2	-0.3	0	0.1	0.2	0.1	0.1	0.1	0.2
SLV-1960	El Salvador	SLV	1960	US Dollar	1935.0	1727.9	2.6	NA	NA	1.3	1713.0	1908.0	1833.1	1611.0	1723.0	NA	NA	10141.4	10527.9	11719.5	16277.7	NA	NA	NA	0.0	1	0.1	0.1	0.1	extrapolated	extrapolated	market	no	NA	NA	0.9	0.1	0.1	0.2	-0.4	0	0.1	0.2	0.1	0.1	0.1	0.2
SLV-1961	El Salvador	SLV	1961	US Dollar	1988.4	1832.7	2.7	NA	NA	1.3	1722.9	1888.9	1898.7	1738.6	1761.3	NA	NA	10299.3	10425.4	11426.5	16665.3	NA	NA	NA	0.0	1	0.1	0.1	0.1	extrapolated	extrapolated	market	no	NA	NA	0.8	0.1	0.1	0.2	-0.3	0	0.1	0.2	0.1	0.1	0.1	0.2
SLV-1962	El Salvador	SLV	1962	US Dollar	2190.9	2056.0	2.8	NA	NA	1.3	1908.8	2075.2	2094.6	2008.4	1795.5	NA	NA	11393.6	11522.7	12500.4	17063.0	NA	NA	NA	0.0	1	0.1	0.1	0.1	extrapolated	extrapolated	market	no	NA	NA	0.8	0.1	0.1	0.2	-0.3	0	0.1	0.2	0.1	0.1	0.1	0.2
SLV-1963	El Salvador	SLV	1963	US Dollar	2263.0	2125.3	2.9	NA	NA	1.3	2000.3	2183.8	2154.5	2091.8	1823.3	NA	NA	11892.1	12173.6	13265.7	17543.1	NA	NA	NA	0.0	1	0.1	0.1	0.1	extrapolated	extrapolated	market	no	NA	NA	0.8	0.1	0.1	0.3	-0.3	0	0.1	0.2	0.1	0.1	0.1	0.2
SLV-1964	El Salvador	SLV	1964	US Dollar	2459.9	2274.7	3.0	NA	NA	1.3	2139.1	2404.7	2332.5	2232.8	1897.5	NA	NA	13026.6	13116.4	14919.8	18561.3	NA	NA	NA	0.1	1	0.1	0.1	0.1	extrapolated	extrapolated	market	no	NA	NA	0.8	0.1	0.1	0.3	-0.3	0	0.1	0.2	0.1	0.1	0.1	0.2
SLV-1965	El Salvador	SLV	1965	US Dollar	2638.4	2413.0	3.1	NA	NA	1.3	2302.3	2551.6	2502.3	2375.6	1983.0	NA	NA	13802.4	14112.0	15722.1	19365.0	NA	NA	NA	0.1	1	0.1	0.1	0.1	extrapolated	extrapolated	market	no	NA	NA	0.8	0.1	0.1	0.2	-0.3	0	0.1	0.2	0.1	0.1	0.1	0.2
SLV-1966	El Salvador	SLV	1966	US Dollar	2809.3	2571.7	3.2	NA	NA	1.3	2499.6	2791.0	2666.6	2550.2	2106.6	NA	NA	14927.1	15302.3	17257.2	20419.5	NA	NA	NA	0.1	1	0.1	0.1	0.1	extrapolated	extrapolated	market	no	NA	NA	0.9	0.1	0.1	0.2	-0.3	0	0.1	0.2	0.1	0.1	0.1	0.2
SLV-1967	El Salvador	SLV	1967	US Dollar	2962.0	2743.2	3.3	NA	NA	1.3	2645.2	2897.4	2824.9	2745.1	2182.8	NA	NA	15570.7	16075.0	17633.5	21093.6	NA	NA	NA	0.1	1	0.1	0.1	0.1	extrapolated	extrapolated	market	no	NA	NA	0.8	0.1	0.1	0.2	-0.3	0	0.1	0.2	0.1	0.1	0.1	0.2
SLV-1968	El Salvador	SLV	1968	US Dollar	2973.3	2871.8	3.4	NA	NA	1.3	2685.8	2881.1	2844.1	2889.2	2199.8	NA	NA	15887.0	16238.4	17227.9	21297.2	NA	NA	NA	0.1	1	0.1	0.1	0.1	extrapolated	extrapolated	market	no	NA	NA	0.8	0.1	0.1	0.3	-0.3	0	0.1	0.2	0.1	0.1	0.1	0.2
SLV-1969	El Salvador	SLV	1969	US Dollar	3072.1	2982.8	3.5	NA	NA	1.3	2770.1	2991.3	2928.2	2991.9	2260.1	NA	NA	16480.5	16726.6	17930.4	21689.3	NA	NA	NA	0.1	1	0.1	0.1	0.1	extrapolated	extrapolated	market	no	NA	NA	0.8	0.1	0.2	0.2	-0.2	0	0.1	0.2	0.1	0.1	0.1	0.2
SLV-1970	El Salvador	SLV	1970	US Dollar	3365.3	3070.2	3.7	NA	NA	1.3	2927.8	3175.9	3199.6	3084.7	2350.4	NA	NA	17229.6	17737.8	19129.1	22254.2	NA	NA	NA	0.1	1	0.1	0.1	0.1	extrapolated	extrapolated	market	no	NA	NA	0.8	0.1	0.2	0.2	-0.2	0	0.1	0.2	0.1	0.1	0.1	0.2
SLV-1971	El Salvador	SLV	1971	US Dollar	3400.1	3162.7	3.8	NA	NA	1.3	2983.5	3288.7	3220.8	3166.8	2453.2	NA	NA	18064.8	18239.4	20145.9	23028.0	NA	NA	NA	0.1	1	0.1	0.1	0.1	extrapolated	extrapolated	market	no	NA	NA	0.8	0.1	0.1	0.2	-0.3	0	0.1	0.2	0.1	0.1	0.1	0.2
SLV-1972	El Salvador	SLV	1972	US Dollar	3625.1	3332.8	3.9	NA	NA	1.3	3142.8	3429.8	3420.3	3342.6	2626.7	NA	NA	19058.4	19195.2	20843.3	24376.7	NA	NA	NA	0.1	1	0.1	0.1	0.1	extrapolated	extrapolated	market	no	NA	NA	0.8	0.1	0.2	0.2	-0.3	0	0.1	0.2	0.1	0.1	0.1	0.2
SLV-1973	El Salvador	SLV	1973	US Dollar	3889.2	3535.1	4.0	NA	NA	1.3	3363.6	3739.7	3641.3	3510.5	2769.8	NA	NA	20023.2	20695.4	23138.5	25351.5	NA	NA	NA	0.1	1	0.1	0.1	0.1	extrapolated	extrapolated	market	no	NA	NA	0.8	0.1	0.2	0.2	-0.3	0	0.1	0.2	0.1	0.2	0.1	0.3
SLV-1974	El Salvador	SLV	1974	US Dollar	3845.1	3708.9	4.1	NA	NA	1.4	3419.4	3909.5	3613.5	3589.1	2981.4	NA	NA	21304.8	21122.9	24593.1	26587.2	NA	NA	NA	0.1	1	0.1	0.1	0.1	extrapolated	extrapolated	market	no	NA	NA	0.8	0.1	0.2	0.3	-0.4	0	0.1	0.2	0.1	0.2	0.2	0.3
SLV-1975	El Salvador	SLV	1975	US Dollar	3991.9	3920.2	4.1	1.2	NA	1.4	3559.1	4010.1	3760.6	3768.4	3251.2	NA	NA	22492.8	21941.9	24788.4	28534.6	NA	NA	NA	0.1	1	0.1	0.2	0.2	extrapolated	extrapolated	market	no	NA	NA	0.8	0.1	0.2	0.3	-0.3	0	0.1	0.3	0.1	0.2	0.2	0.3
SLV-1976	El Salvador	SLV	1976	US Dollar	4631.0	4075.1	4.2	1.3	NA	1.4	3937.2	4431.4	4343.8	3940.4	3467.6	NA	NA	23378.4	24298.5	27443.9	30453.1	NA	NA	NA	0.1	1	0.2	0.2	0.2	extrapolated	extrapolated	market	no	NA	NA	0.8	0.1	0.2	0.2	-0.4	0	0.2	0.3	0.1	0.3	0.2	0.4
SLV-1977	El Salvador	SLV	1977	US Dollar	5449.4	4217.1	4.3	1.3	NA	1.4	4365.6	5064.4	5118.7	4090.6	3840.4	NA	NA	24789.6	26910.2	32121.7	33198.9	NA	NA	NA	0.1	1	0.2	0.2	0.2	extrapolated	extrapolated	market	no	NA	NA	0.9	0.2	0.2	0.2	-0.4	0	0.2	0.3	0.1	0.4	0.2	0.4
SLV-1978	El Salvador	SLV	1978	US Dollar	5117.9	4515.6	4.4	1.4	NA	1.4	4523.7	5243.2	4799.0	4355.5	4239.0	NA	NA	26388.0	27856.9	33214.9	35825.1	NA	NA	NA	0.1	1	0.2	0.2	0.2	extrapolated	extrapolated	market	no	NA	NA	0.8	0.2	0.2	0.2	-0.4	0	0.2	0.3	0.2	0.3	0.2	0.4
SLV-1979	El Salvador	SLV	1979	US Dollar	5126.8	4554.5	4.5	1.4	NA	1.4	4269.3	4817.5	4809.2	4363.9	4503.1	NA	NA	25934.4	26117.2	29952.8	37426.4	NA	NA	NA	0.1	1	0.2	0.2	0.3	extrapolated	extrapolated	market	no	NA	NA	0.8	0.1	0.2	0.3	-0.4	0	0.2	0.4	0.2	0.3	0.2	0.4
SLV-1980	El Salvador	SLV	1980	US Dollar	4649.4	4278.8	4.6	1.4	NA	1.4	3981.8	4354.7	4395.1	4056.5	4601.4	NA	NA	23680.8	24121.2	26371.4	37785.8	NA	NA	NA	0.1	1	0.3	0.3	0.3	benchmark	extrapolated	market	no	0.5	NA	0.8	0.1	0.2	0.3	-0.4	0	0.3	0.4	0.2	0.3	0.3	0.4
SLV-1981	El Salvador	SLV	1981	US Dollar	4158.9	4066.8	4.7	1.4	NA	1.4	3844.3	4213.6	3941.5	3838.3	4800.8	NA	NA	21722.4	22492.0	24689.9	37937.4	NA	NA	NA	0.1	1	0.3	0.3	0.3	interpolated	extrapolated	market	no	NA	NA	0.8	0.1	0.2	0.2	-0.3	0	0.3	0.4	0.2	0.3	0.3	0.5
SLV-1982	El Salvador	SLV	1982	US Dollar	4018.6	4018.7	4.7	1.4	NA	1.5	3696.3	4042.0	3824.0	3818.8	4955.2	NA	NA	20505.6	20884.3	22829.7	37910.2	NA	NA	NA	0.1	1	0.3	0.3	0.3	interpolated	extrapolated	market	no	NA	NA	0.7	0.1	0.2	0.2	-0.3	0	0.3	0.5	0.2	0.3	0.3	0.5
SLV-1983	El Salvador	SLV	1983	US Dollar	4132.6	4157.7	4.8	1.4	NA	1.5	3822.9	4145.3	3932.3	3985.5	4915.6	NA	NA	20664.0	21008.3	22708.6	37828.4	NA	NA	NA	0.1	1	0.3	0.3	0.3	interpolated	extrapolated	market	no	NA	NA	0.7	0.1	0.2	0.2	-0.3	0	0.4	0.5	0.2	0.3	0.4	0.5
SLV-1984	El Salvador	SLV	1984	US Dollar	4359.0	4385.9	4.9	1.4	NA	1.5	4078.1	4414.8	4134.6	4203.6	5056.1	NA	NA	21139.2	21835.7	23572.5	37889.2	NA	NA	NA	0.1	1	0.4	0.4	0.4	interpolated	benchmark	market	no	NA	NA	0.7	0.1	0.2	0.2	-0.3	0	0.4	0.5	0.3	0.4	0.4	0.6
SLV-1985	El Salvador	SLV	1985	US Dollar	4607.5	4457.2	4.9	1.4	NA	1.5	4401.0	4728.1	4395.9	4341.9	5212.9	NA	NA	21556.8	22713.4	24274.5	38249.9	NA	NA	NA	0.1	1	0.4	0.4	0.4	interpolated	benchmark	market	no	NA	NA	0.8	0.1	0.2	0.3	-0.3	0	0.5	0.6	0.3	0.4	0.4	0.7
SLV-1986	El Salvador	SLV	1986	US Dollar	4992.9	4838.0	5.0	1.4	NA	1.5	4592.7	4999.5	4789.9	4753.4	5513.2	NA	NA	21693.6	22798.4	24897.8	38841.2	NA	NA	NA	0.1	1	0.5	0.5	0.5	interpolated	benchmark	market	no	NA	NA	0.7	0.1	0.2	0.3	-0.4	0	0.6	0.8	0.3	0.4	0.4	0.9
SLV-1987	El Salvador	SLV	1987	US Dollar	5051.6	4840.5	5.1	1.5	NA	1.6	4786.6	5187.2	4842.9	4730.8	5833.6	NA	NA	22276.8	23019.1	24972.5	39691.3	NA	NA	NA	0.1	1	0.6	0.6	0.6	interpolated	benchmark	market	no	NA	NA	0.8	0.1	0.3	0.3	-0.4	0	0.7	0.9	0.3	0.5	0.5	1.0
SLV-1988	El Salvador	SLV	1988	US Dollar	5382.8	5085.7	5.1	1.5	NA	1.6	5001.6	5500.9	5166.4	4977.9	6169.6	NA	NA	22636.8	23238.7	25760.6	40608.0	NA	NA	NA	0.1	1	0.7	0.7	0.7	interpolated	benchmark	market	no	NA	NA	0.7	0.1	0.3	0.2	-0.3	0	0.8	0.9	0.4	0.5	0.5	1.0
SLV-1989	El Salvador	SLV	1989	US Dollar	5545.0	5135.8	5.2	1.6	NA	1.6	5268.3	5894.9	5337.0	5043.7	6527.5	NA	NA	22874.4	23690.6	26922.2	41774.4	NA	NA	NA	0.1	1	0.8	0.8	0.8	interpolated	benchmark	market	no	NA	NA	0.8	0.1	0.3	0.2	-0.4	0	0.9	1.0	0.4	0.5	0.5	1.1
SLV-1990	El Salvador	SLV	1990	US Dollar	5535.1	4805.5	5.3	1.7	NA	1.6	5606.0	6046.1	5366.2	4701.3	6861.5	NA	NA	23652.0	24139.1	26146.8	42318.5	NA	NA	NA	0.1	1	0.8	0.9	1.0	interpolated	benchmark	market	no	NA	NA	0.9	0.1	0.3	0.4	-0.7	0	1.0	1.5	0.4	0.5	0.5	1.5
SLV-1991	El Salvador	SLV	1991	US Dollar	5936.1	4939.2	5.3	1.7	NA	1.7	5953.3	6498.0	5734.9	4986.1	7202.9	NA	NA	24497.9	24876.0	27400.7	43371.3	NA	NA	NA	0.0	1	0.9	0.9	1.1	interpolated	benchmark	market	no	NA	NA	0.9	0.1	0.3	0.3	-0.6	0	1.0	1.5	0.4	0.5	0.5	1.5
SLV-1992	El Salvador	SLV	1992	US Dollar	6504.2	5411.8	5.4	1.8	NA	1.7	6571.2	7304.6	6278.4	5206.1	7687.2	NA	NA	26345.8	26750.5	30236.2	45022.5	NA	NA	NA	0.0	1	0.9	0.9	1.1	interpolated	benchmark	market	no	NA	NA	1.0	0.1	0.3	0.4	-0.8	0	1.0	1.5	0.4	0.5	0.5	1.6
SLV-1993	El Salvador	SLV	1993	US Dollar	7346.2	6345.9	5.5	1.9	NA	1.7	7273.7	8122.3	7078.1	6101.3	8461.3	NA	NA	28287.4	28806.2	32671.1	47214.1	NA	NA	NA	0.0	1	0.9	1.0	1.1	interpolated	benchmark	market	no	NA	NA	1.0	0.1	0.2	0.4	-0.8	0	1.0	1.5	0.4	0.5	0.5	1.6
SLV-1994	El Salvador	SLV	1994	US Dollar	8207.6	6780.7	5.5	2.0	NA	1.7	8116.9	9098.4	7895.2	6775.1	9419.2	NA	NA	29998.9	30968.7	35479.2	49824.1	NA	NA	NA	0.0	1	1.0	1.0	1.2	interpolated	benchmark	market	no	NA	NA	1.0	0.1	0.2	0.5	-0.8	0	1.1	1.6	0.5	0.5	0.5	1.6
SLV-1995	El Salvador	SLV	1995	US Dollar	9318.7	7888.3	5.6	2.0	NA	1.8	9281.1	10435.2	8986.6	7913.0	10640.5	NA	NA	31917.8	33815.8	39097.1	53000.3	NA	NA	NA	0.1	1	1.0	1.1	1.2	interpolated	benchmark	market	no	NA	NA	1.0	0.1	0.2	0.5	-0.8	0	1.1	1.6	0.5	0.5	0.6	1.6
SLV-1996	El Salvador	SLV	1996	US Dollar	9934.7	8648.7	5.6	2.0	NA	1.8	9901.1	10819.8	9587.3	8671.4	11636.6	NA	NA	32462.1	34372.5	38158.6	55270.5	NA	NA	NA	0.0	1	1.0	1.1	1.2	interpolated	benchmark	market	no	NA	NA	1.0	0.1	0.2	0.5	-0.7	0	1.1	1.7	0.6	0.5	0.6	1.6
SLV-1997	El Salvador	SLV	1997	US Dollar	10865.0	9510.3	5.7	2.0	NA	1.8	10656.5	11679.9	10460.3	9594.2	12896.6	NA	NA	33840.6	35405.3	39482.6	57859.7	NA	NA	NA	0.0	1	1.0	1.1	1.2	interpolated	benchmark	market	no	NA	NA	0.9	0.1	0.2	0.6	-0.8	0	1.1	1.6	0.6	0.5	0.5	1.5
SLV-1998	El Salvador	SLV	1998	US Dollar	11822.4	9966.7	5.7	2.1	NA	1.8	11420.5	12730.7	11336.9	10310.1	14480.6	NA	NA	35109.2	36252.9	41511.2	60866.6	NA	NA	NA	0.0	1	1.0	1.1	1.2	interpolated	benchmark	market	no	NA	NA	0.9	0.1	0.2	0.6	-0.8	0	1.1	1.6	0.6	0.5	0.5	1.4
SLV-1999	El Salvador	SLV	1999	US Dollar	12738.6	10614.2	5.8	2.1	NA	1.9	12412.8	13745.8	12235.4	11020.9	16210.3	NA	NA	36320.1	37471.4	42427.1	63673.3	NA	NA	NA	0.0	1	1.0	1.0	1.1	interpolated	benchmark	market	no	NA	66.7	0.9	0.1	0.2	0.6	-0.8	0	1.0	1.5	0.6	0.5	0.5	1.4
SLV-2000	El Salvador	SLV	2000	US Dollar	13578.5	11809.7	5.8	2.2	NA	1.9	13529.3	15016.8	13054.3	11989.0	18214.9	NA	NA	37102.0	38822.0	43901.1	66648.9	NA	NA	NA	0.0	1	1.0	1.0	1.1	interpolated	benchmark	market	no	NA	NA	0.9	0.1	0.2	0.7	-0.9	0	1.0	1.5	0.6	0.5	0.5	1.3
SLV-2001	El Salvador	SLV	2001	US Dollar	14789.4	12413.9	5.8	2.2	NA	1.9	14839.5	16534.2	14277.9	12443.0	20437.5	NA	NA	37736.0	40093.4	45452.2	69572.9	NA	NA	NA	0.0	1	0.9	1.0	1.1	interpolated	benchmark	market	no	NA	NA	1.0	0.1	0.2	0.6	-1.0	0	1.0	1.4	0.6	0.4	0.5	1.2
SLV-2002	El Salvador	SLV	2002	US Dollar	16034.2	13837.7	5.9	2.2	NA	1.9	15961.1	17768.1	15489.5	13999.2	22973.8	NA	NA	38619.3	40673.9	45837.0	72607.6	NA	NA	NA	0.0	1	0.9	0.9	1.0	interpolated	benchmark	market	no	NA	NA	1.0	0.1	0.2	0.6	-0.9	0	0.9	1.3	0.6	0.5	0.5	1.2
SLV-2003	El Salvador	SLV	2003	US Dollar	17350.3	15385.3	5.9	2.2	NA	1.9	17365.4	19451.2	16781.8	15672.6	26116.7	NA	NA	39507.7	41409.5	47055.9	75721.6	NA	NA	NA	0.0	1	0.9	0.9	1.0	interpolated	benchmark	market	no	NA	NA	0.9	0.1	0.2	0.5	-0.8	0	0.9	1.2	0.6	0.5	0.5	1.1
SLV-2004	El Salvador	SLV	2004	US Dollar	18765.1	16650.4	5.9	2.2	NA	1.9	19149.9	21319.1	18169.0	16952.9	30179.8	NA	NA	40238.8	42535.2	47876.0	78393.3	NA	NA	NA	0.0	1	0.8	0.9	0.9	interpolated	benchmark	market	no	NA	68.3	1.0	0.1	0.2	0.5	-0.7	0	0.9	1.2	0.5	0.5	0.6	1.0
SLV-2005	El Salvador	SLV	2005	US Dollar	20962.3	19788.2	5.9	2.2	NA	1.9	22115.6	24575.9	20735.3	19766.1	35501.4	NA	NA	41672.3	44661.0	50177.7	81070.2	NA	NA	NA	0.0	1	0.8	0.8	0.9	interpolated	benchmark	market	no	NA	71.7	1.0	0.1	0.2	0.4	-0.7	0	0.8	1.1	0.5	0.5	0.6	0.9
SLV-2006	El Salvador	SLV	2006	US Dollar	23670.1	22070.8	6.0	2.3	NA	2.0	25040.7	28038.2	23271.1	22347.1	42250.0	NA	NA	43302.6	46758.6	53000.1	84467.6	NA	NA	NA	0.0	1	0.8	0.8	0.8	interpolated	benchmark	market	no	NA	71.7	1.0	0.1	0.1	0.4	-0.6	0	0.8	1.0	0.5	0.6	0.6	0.8
SLV-2007	El Salvador	SLV	2007	US Dollar	26954.1	25463.7	6.0	2.4	NA	2.0	29046.2	32438.3	26499.2	25836.9	49601.4	NA	NA	44965.5	49451.0	55837.3	88289.6	NA	NA	NA	0.0	1	0.7	0.8	0.8	interpolated	benchmark	market	no	NA	73.3	1.0	0.1	0.1	0.3	-0.6	0	0.8	1.0	0.5	0.6	0.6	0.7
SLV-2008	El Salvador	SLV	2008	US Dollar	30053.3	28863.7	6.0	2.4	NA	2.0	33050.3	36672.1	29859.2	28644.2	57652.1	NA	NA	45538.1	50258.5	56225.4	91446.3	NA	NA	NA	0.0	1	0.7	0.7	0.7	interpolated	benchmark	market	no	NA	83.3	1.0	0.1	0.1	0.3	-0.6	0	0.7	0.9	0.5	0.7	0.7	0.7
SLV-2009	El Salvador	SLV	2009	US Dollar	32585.9	31136.0	6.0	2.4	NA	2.0	33882.8	37215.6	32227.4	31383.5	66042.6	NA	NA	44111.4	45806.5	50506.8	92998.6	NA	NA	NA	0.0	1	0.6	0.6	0.7	interpolated	benchmark	market	no	NA	83.3	0.9	0.1	0.1	0.2	-0.4	0	0.6	0.8	0.5	0.7	0.6	0.7
SLV-2010	El Salvador	SLV	2010	US Dollar	37684.8	37108.7	6.0	2.4	NA	2.0	39829.3	43812.2	37471.9	37264.9	77955.6	NA	NA	44713.6	46830.7	51644.9	94734.9	NA	NA	NA	0.0	1	0.6	0.6	0.6	interpolated	benchmark	market	no	NA	90.0	0.9	0.1	0.1	0.2	-0.4	0	0.6	0.7	0.5	0.7	0.6	0.6
SLV-2011	El Salvador	SLV	2011	US Dollar	45166.8	45704.8	6.1	2.4	NA	2.0	48017.3	53605.3	45166.8	45704.8	97264.7	NA	NA	45704.8	48017.3	53605.3	97264.7	NA	NA	NA	0.0	1	0.5	0.5	0.5	benchmark	benchmark	market	no	0.6	85.6	0.9	0.1	0.1	0.2	-0.4	0	0.5	0.6	0.5	0.7	0.6	0.5
SLV-2012	El Salvador	SLV	2012	US Dollar	46164.4	47179.4	6.1	2.5	NA	2.1	49225.0	54663.9	46147.6	46956.7	99345.6	NA	NA	46564.6	49170.9	54642.7	99598.2	NA	NA	NA	0.0	1	0.5	0.5	0.5	extrapolated	benchmark	market	no	NA	91.0	0.9	0.1	0.1	0.2	-0.4	0	0.5	0.6	0.5	0.7	0.6	0.5
SLV-2013	El Salvador	SLV	2013	US Dollar	46742.5	47393.0	6.1	2.6	NA	2.1	49761.2	55572.1	46618.4	47147.3	103172.3	NA	NA	47424.4	49694.7	55754.1	102483.9	NA	NA	NA	0.0	1	0.5	0.5	0.5	extrapolated	benchmark	market	no	NA	91.1	0.9	0.1	0.1	0.2	-0.4	0	0.5	0.6	0.5	0.7	0.6	0.5
SLV-2014	El Salvador	SLV	2014	US Dollar	47903.3	48970.3	6.1	2.6	NA	2.1	50944.9	56342.7	47846.7	48643.6	107174.8	NA	NA	48350.4	50767.7	56361.1	104730.7	NA	NA	NA	0.0	1	0.5	0.5	0.5	extrapolated	benchmark	market	no	NA	91.1	0.9	0.1	0.1	0.2	-0.3	0	0.5	0.6	0.6	0.7	0.6	0.5

2- Construya una función que le permita elegir todas las variables de la categoria “Trade detail”, muestre su uso para los datos de Argentina

funcion_variable_trade_detail_c1 <- function(country,anio_inicio_1,anio_final_1) {
  pwt9.0 %>% filter(country==!!country,
                    year>=anio_inicio_1,
                    year<=anio_final_1) %>%
    select(country,
           year, 
           pl_x,pl_m,
           csh_x,csh_m)-> pais_periodo_2
  pais_periodo_2
}
funcion_variable_trade_detail_c1(country = "Argentina",anio_inicio_1  = 1950,anio_final_1 = 2014) %>%
 kable(caption = "Datos de Argentina para la variable Trade detail periodo 1950-2014",
 digits = 1,align = "l") %>%
 kable_styling(bootstrap_options = "striped",
 full_width = TRUE)

Datos de Argentina para la variable Trade detail periodo 1950-2014

	country	year	pl_x	pl_m	csh_x	csh_m
ARG-1950	Argentina	1950	0.1	0.1	0.1	-0.1
ARG-1951	Argentina	1951	0.2	0.1	0.1	-0.1
ARG-1952	Argentina	1952	0.1	0.1	0.1	-0.1
ARG-1953	Argentina	1953	0.1	0.1	0.1	0.0
ARG-1954	Argentina	1954	0.1	0.1	0.1	0.0
ARG-1955	Argentina	1955	0.1	0.1	0.1	-0.1
ARG-1956	Argentina	1956	0.2	0.2	0.1	0.0
ARG-1957	Argentina	1957	0.2	0.2	0.1	0.0
ARG-1958	Argentina	1958	0.2	0.2	0.1	0.0
ARG-1959	Argentina	1959	0.2	0.3	0.1	0.0
ARG-1960	Argentina	1960	0.2	0.2	0.1	-0.1
ARG-1961	Argentina	1961	0.2	0.2	0.1	-0.1
ARG-1962	Argentina	1962	0.1	0.3	0.1	-0.1
ARG-1963	Argentina	1963	0.2	0.3	0.1	0.0
ARG-1964	Argentina	1964	0.2	0.2	0.1	-0.1
ARG-1965	Argentina	1965	0.2	0.2	0.1	-0.1
ARG-1966	Argentina	1966	0.2	0.2	0.1	0.0
ARG-1967	Argentina	1967	0.2	0.3	0.1	0.0
ARG-1968	Argentina	1968	0.3	0.3	0.1	0.0
ARG-1969	Argentina	1969	0.2	0.3	0.1	0.0
ARG-1970	Argentina	1970	0.2	0.3	0.1	-0.1
ARG-1971	Argentina	1971	0.3	0.3	0.1	-0.1
ARG-1972	Argentina	1972	0.3	0.4	0.0	0.0
ARG-1973	Argentina	1973	0.3	0.3	0.0	0.0
ARG-1974	Argentina	1974	0.3	0.3	0.0	0.0
ARG-1975	Argentina	1975	0.3	0.3	0.1	-0.1
ARG-1976	Argentina	1976	0.3	0.4	0.1	0.0
ARG-1977	Argentina	1977	0.3	0.5	0.1	-0.1
ARG-1978	Argentina	1978	0.3	0.4	0.1	-0.1
ARG-1979	Argentina	1979	0.2	0.3	0.1	-0.1
ARG-1980	Argentina	1980	0.2	0.2	0.1	-0.1
ARG-1981	Argentina	1981	0.3	0.3	0.1	-0.1
ARG-1982	Argentina	1982	0.4	0.5	0.1	-0.1
ARG-1983	Argentina	1983	0.4	0.5	0.1	-0.1
ARG-1984	Argentina	1984	0.4	0.4	0.1	-0.1
ARG-1985	Argentina	1985	0.4	0.4	0.2	-0.1
ARG-1986	Argentina	1986	0.4	0.5	0.1	-0.1
ARG-1987	Argentina	1987	0.5	0.5	0.1	-0.1
ARG-1988	Argentina	1988	0.5	0.5	0.1	-0.1
ARG-1989	Argentina	1989	0.5	0.5	0.1	0.0
ARG-1990	Argentina	1990	0.5	0.5	0.1	0.0
ARG-1991	Argentina	1991	0.6	0.6	0.1	-0.1
ARG-1992	Argentina	1992	0.5	0.5	0.1	-0.1
ARG-1993	Argentina	1993	0.5	0.5	0.1	-0.1
ARG-1994	Argentina	1994	0.5	0.6	0.1	-0.1
ARG-1995	Argentina	1995	0.6	0.6	0.1	-0.1
ARG-1996	Argentina	1996	0.6	0.6	0.1	-0.1
ARG-1997	Argentina	1997	0.6	0.6	0.1	-0.1
ARG-1998	Argentina	1998	0.5	0.5	0.1	-0.1
ARG-1999	Argentina	1999	0.5	0.5	0.1	-0.1
ARG-2000	Argentina	2000	0.5	0.5	0.1	-0.1
ARG-2001	Argentina	2001	0.5	0.5	0.1	-0.1
ARG-2002	Argentina	2002	0.5	0.5	0.1	0.0
ARG-2003	Argentina	2003	0.5	0.5	0.1	-0.1
ARG-2004	Argentina	2004	0.6	0.5	0.1	-0.1
ARG-2005	Argentina	2005	0.6	0.6	0.1	-0.1
ARG-2006	Argentina	2006	0.6	0.6	0.1	-0.1
ARG-2007	Argentina	2007	0.7	0.6	0.1	-0.1
ARG-2008	Argentina	2008	0.7	0.7	0.1	-0.1
ARG-2009	Argentina	2009	0.7	0.6	0.1	-0.1
ARG-2010	Argentina	2010	0.7	0.7	0.1	-0.1
ARG-2011	Argentina	2011	0.8	0.7	0.1	-0.1
ARG-2012	Argentina	2012	0.7	0.7	0.1	-0.1
ARG-2013	Argentina	2013	0.8	0.7	0.1	-0.1
ARG-2014	Argentina	2014	0.7	0.7	0.1	-0.1

3- Use las funciones creadas en 1 y 2, para generar 2 dataframes, que muestren los datos de “México” y “Canadá” para el periodo 2000-2014

dataframe1<-funcion_filtro_pais_c1(country = c("Mexico","Canada"),anio_inicio = 2000,anio_final = 2014) 
print(dataframe1)

##          country isocode year        currency   rgdpe   rgdpo       pop
## CAN-2001  Canada     CAN 2001 Canadian Dollar 1166188 1119308  30.99134
## CAN-2003  Canada     CAN 2003 Canadian Dollar 1211094 1184269  31.59659
## CAN-2005  Canada     CAN 2005 Canadian Dollar 1311424 1323181  32.25633
## CAN-2007  Canada     CAN 2007 Canadian Dollar 1376870 1384391  32.98228
## CAN-2009  Canada     CAN 2009 Canadian Dollar 1310934 1304883  33.74656
## CAN-2011  Canada     CAN 2011 Canadian Dollar 1423920 1455816  34.49990
## CAN-2013  Canada     CAN 2013 Canadian Dollar 1478439 1493624  35.23061
## MEX-2000  Mexico     MEX 2000    Mexican Peso 1241567 1203299 102.80859
## MEX-2002  Mexico     MEX 2002    Mexican Peso 1265801 1217542 105.57830
## MEX-2004  Mexico     MEX 2004    Mexican Peso 1399936 1345215 108.25782
## MEX-2006  Mexico     MEX 2006    Mexican Peso 1581637 1542631 111.38286
## MEX-2008  Mexico     MEX 2008    Mexican Peso 1693705 1677677 114.97282
## MEX-2010  Mexico     MEX 2010    Mexican Peso 1734610 1694514 118.61754
## MEX-2012  Mexico     MEX 2012    Mexican Peso 1908250 1862729 122.07096
## MEX-2014  Mexico     MEX 2014    Mexican Peso 1987688 1945966 125.38583
##               emp      avh       hc      ccon     cda   cgdpe   cgdpo      ck
## CAN-2001 15.05903 1767.990 3.518916  814203.9 1079932 1145022 1144414 3268334
## CAN-2003 15.84749 1732.136 3.548723  858441.9 1148489 1194611 1200543 3349291
## CAN-2005 16.43793 1739.182 3.578782  918976.9 1263380 1315081 1326233 3865556
## CAN-2007 17.26695 1724.689 3.609095  969776.7 1342214 1370408 1395106 4445640
## CAN-2009 17.43560 1678.515 3.639666 1000717.9 1325223 1306457 1323073 4794360
## CAN-2011 18.07691 1683.574 3.662325 1045868.8 1440603 1423920 1455816 5427466
## CAN-2013 18.66565 1682.736 3.676923 1086339.8 1488701 1465085 1472069 5828469
## MEX-2000 38.60970 2173.992 2.417732  976115.5 1233276 1210525 1196573 2683662
## MEX-2002 39.59854 2196.150 2.456598 1021844.4 1259728 1243224 1219592 2552782
## MEX-2004 41.23692 2123.364 2.496088 1114709.0 1384239 1376237 1344221 3077106
## MEX-2006 43.06945 2141.324 2.536212 1244907.5 1576208 1571088 1546752 3770402
## MEX-2008 45.01016 2173.356 2.571415 1345486.1 1729921 1692513 1672410 4036200
## MEX-2010 48.29945 2128.041 2.599173 1381195.4 1742997 1728535 1697135 5054693
## MEX-2012 50.82909 2106.862 2.637690 1535906.1 1947835 1903657 1851572 6089364
## MEX-2014 51.41257 2136.773 2.676779 1602949.4 2009978 1974138 1934006 6677512
##               ctfp     cwtfp  rgdpna    rconna   rdana    rkna    rtfpna
## CAN-2001 0.9022754 0.8153173 1190649  782785.5 1041029 3905941 1.0337603
## CAN-2003 0.8915871 0.8093318 1247575  832796.8 1119539 4151862 1.0330168
## CAN-2005 0.9038564 0.7981808 1327435  882079.1 1221829 4462552 1.0369463
## CAN-2007 0.8834894 0.8020070 1389595  950916.3 1319552 4812567 1.0226208
## CAN-2009 0.8118237 0.7897093 1367808  994270.1 1323141 5106391 0.9890912
## CAN-2011 0.8070218 0.7662106 1455816 1045868.8 1440603 5427466 1.0000000
## CAN-2013 0.7754062 0.7574083 1513537 1084256.5 1500049 5779532 0.9928653
## MEX-2000 0.6776875 0.6711588 1458667 1084404.0 1414794 3850000 1.1481084
## MEX-2002 0.6798000 0.6677148 1469444 1119252.6 1433203 4150159 1.0850003
## MEX-2004 0.6890303 0.6691776 1552597 1225134.2 1551886 4461555 1.0916569
## MEX-2006 0.7279464 0.6927031 1679987 1343449.2 1719133 4852529 1.0932913
## MEX-2008 0.7459487 0.7331457 1758094 1411593.2 1826431 5305337 1.0535300
## MEX-2010 0.6361806 0.6299252 1761765 1405425.9 1779081 5671746 0.9895102
## MEX-2012 0.6145336 0.6213605 1904764 1537147.2 1954599 6096434 1.0019095
## MEX-2014 0.6035797 0.6044779 1974418 1601032.4 2025506 6498114 0.9832620
##            rwtfpna     labsh      delta         xr    pl_con     pl_da
## CAN-2001 0.9134005 0.6171623 0.04350585  1.5487608 0.6702421 0.6399313
## CAN-2003 0.9367892 0.6124471 0.04180438  1.4010517 0.7807368 0.7431563
## CAN-2005 0.9645296 0.5987505 0.04020973  1.2117633 0.9279599 0.8852534
## CAN-2007 0.9813300 0.6059821 0.03873762  1.0740992 1.1123220 1.0638244
## CAN-2009 0.9668959 0.6315947 0.03881708  1.1431006 1.0911957 1.0492800
## CAN-2011 1.0000000 0.6074459 0.03708802  0.9895307 1.3175685 1.2562085
## CAN-2013 0.9944088 0.6191180 0.03645137  1.0297966 1.3056631 1.2551931
## MEX-2000 1.0948994 0.4670270 0.04038701  9.4555583 0.5079750 0.5357581
## MEX-2002 1.0404917 0.4771637 0.03962168  9.6559583 0.5620881 0.5825984
## MEX-2004 1.0728562 0.4381100 0.03732139 11.2859667 0.5380411 0.5595008
## MEX-2006 1.1000023 0.4061596 0.03668293 10.8992417 0.5956349 0.6144006
## MEX-2008 1.0761238 0.3901641 0.03644980 11.1297167 0.6365756 0.6506737
## MEX-2010 0.9824765 0.4086950 0.03668989 12.6360083 0.5986645 0.6074073
## MEX-2012 1.0108787 0.3860400 0.03684472 13.1694583 0.6110190 0.6222254
## MEX-2014 0.9917858 0.3860400 0.03734821 13.2924500 0.6468756 0.6558278
##            pl_gdpo        i_cig      i_xm   i_xr i_outlier   cor_exp  statcap
## CAN-2001 0.6402714 interpolated benchmark market        no        NA       NA
## CAN-2003 0.7394839 interpolated benchmark market        no        NA       NA
## CAN-2005 0.8778094    benchmark benchmark market        no 0.9038276       NA
## CAN-2007 1.0449910 interpolated benchmark market        no        NA       NA
## CAN-2009 1.0361022 interpolated benchmark market        no        NA       NA
## CAN-2011 1.2286866    benchmark benchmark market        no 0.8238315       NA
## CAN-2013 1.2492380 extrapolated benchmark market        no        NA       NA
## MEX-2000 0.5420051 interpolated benchmark market        no        NA       NA
## MEX-2002 0.5938877    benchmark benchmark market        no        NA       NA
## MEX-2004 0.5728266 interpolated benchmark market        no        NA 74.44444
## MEX-2006 0.6240674 interpolated benchmark market        no        NA 68.88889
## MEX-2008 0.6584950 interpolated benchmark market        no        NA 77.77778
## MEX-2010 0.6186453 interpolated benchmark market        no        NA 85.55556
## MEX-2012 0.6397288 extrapolated benchmark market        no        NA 88.00000
## MEX-2014 0.6694366 extrapolated benchmark market        no        NA 85.55556
##              csh_c     csh_i     csh_g     csh_x      csh_m         csh_r
## CAN-2001 0.5601038 0.2321958 0.1513555 0.4177729 -0.3644541  0.0030260538
## CAN-2003 0.5621071 0.2415964 0.1529374 0.3902732 -0.3496419  0.0027277917
## CAN-2005 0.5438991 0.2596853 0.1490238 0.4328717 -0.3851879 -0.0002920294
## CAN-2007 0.5394937 0.2669595 0.1556341 0.4428070 -0.3985552 -0.0063390261
## CAN-2009 0.5724548 0.2452664 0.1839038 0.3453314 -0.3370062 -0.0099502383
## CAN-2011 0.5405646 0.2711428 0.1778429 0.4387028 -0.4166212 -0.0116318641
## CAN-2013 0.5595505 0.2733303 0.1784177 0.4206315 -0.4186161 -0.0133138811
## MEX-2000 0.6732539 0.2149140 0.1425054 0.2626764 -0.2947699  0.0014201968
## MEX-2002 0.6941089 0.1950519 0.1437490 0.2504522 -0.2809940 -0.0023679789
## MEX-2004 0.6979996 0.2005101 0.1312609 0.2391311 -0.2745519  0.0056501571
## MEX-2006 0.6725003 0.2141908 0.1323524 0.2579798 -0.2801102  0.0030869977
## MEX-2008 0.6508341 0.2298687 0.1536851 0.2416872 -0.2696986 -0.0063766162
## MEX-2010 0.6285632 0.2131835 0.1852762 0.2481539 -0.2698361 -0.0053406847
## MEX-2012 0.6352695 0.2224750 0.1942454 0.2695678 -0.2984421 -0.0231155679
## MEX-2014 0.6356119 0.2104586 0.1932114 0.2715108 -0.2945466 -0.0162459742
##               pl_c      pl_i      pl_g      pl_x      pl_m      pl_k
## CAN-2001 0.6292517 0.5470572 0.8219304 0.5460286 0.5313601 0.6292847
## CAN-2003 0.7315946 0.6319304 0.9613546 0.5810179 0.5726507 0.7568532
## CAN-2005 0.8729587 0.7712987 1.1287004 0.6280424 0.6155325 0.8875628
## CAN-2007 1.0543412 0.9375428 1.3133082 0.6796820 0.6845841 1.0519462
## CAN-2009 1.0351254 0.9200191 1.2657314 0.6898180 0.7204297 1.0221647
## CAN-2011 1.2595756 1.0936318 1.4938417 0.7052622 0.7428895 1.1579119
## CAN-2013 1.2401137 1.1189287 1.5112380 0.7374130 0.7493351 1.1488672
## MEX-2000 0.5336822 0.6412158 0.3865237 0.5290740 0.5086392 0.6657988
## MEX-2002 0.5839284 0.6707015 0.4566301 0.5262772 0.4921273 0.8063704
## MEX-2004 0.5515599 0.6482526 0.4661525 0.5847969 0.5332708 0.7196133
## MEX-2006 0.6152702 0.6849153 0.4958651 0.6264205 0.5910664 0.7278860
## MEX-2008 0.6767916 0.7000160 0.4662665 0.7205961 0.6841487 0.8066145
## MEX-2010 0.6602539 0.6407837 0.3897180 0.7083094 0.6583319 0.6478299
## MEX-2012 0.6784819 0.6640091 0.3903852 0.7425870 0.6709370 0.6141177
## MEX-2014 0.7153954 0.6910835 0.4214644 0.7570050 0.7021390 0.6044782

dataframe_1<-funcion_variable_trade_detail_c1(country = c("Mexico","Canada"),anio_inicio_1 = 2000,anio_final_1=2014)
print(dataframe_1)

##          country year      pl_x      pl_m     csh_x      csh_m
## CAN-2001  Canada 2001 0.5460286 0.5313601 0.4177729 -0.3644541
## CAN-2003  Canada 2003 0.5810179 0.5726507 0.3902732 -0.3496419
## CAN-2005  Canada 2005 0.6280424 0.6155325 0.4328717 -0.3851879
## CAN-2007  Canada 2007 0.6796820 0.6845841 0.4428070 -0.3985552
## CAN-2009  Canada 2009 0.6898180 0.7204297 0.3453314 -0.3370062
## CAN-2011  Canada 2011 0.7052622 0.7428895 0.4387028 -0.4166212
## CAN-2013  Canada 2013 0.7374130 0.7493351 0.4206315 -0.4186161
## MEX-2000  Mexico 2000 0.5290740 0.5086392 0.2626764 -0.2947699
## MEX-2002  Mexico 2002 0.5262772 0.4921273 0.2504522 -0.2809940
## MEX-2004  Mexico 2004 0.5847969 0.5332708 0.2391311 -0.2745519
## MEX-2006  Mexico 2006 0.6264205 0.5910664 0.2579798 -0.2801102
## MEX-2008  Mexico 2008 0.7205961 0.6841487 0.2416872 -0.2696986
## MEX-2010  Mexico 2010 0.7083094 0.6583319 0.2481539 -0.2698361
## MEX-2012  Mexico 2012 0.7425870 0.6709370 0.2695678 -0.2984421
## MEX-2014  Mexico 2014 0.7570050 0.7021390 0.2715108 -0.2945466

Clave 2

1- Construya una función que le permita elegir el país y filtrar para un periodo(inicio,final), muestre su uso filtrando los datos para Guatemala , en el periodo de 1990-2014.

library(dplyr)
library(kableExtra)
options(scipen = 999999)
funcion_filtro_pais_c2 <- function(country,anio_inicio_2,anio_final_2) {
  pwt9.0 %>% filter(country==!!country,
year>=anio_inicio_2,year<=anio_final_2) -> pais_periodo_3
  pais_periodo_3
}
funcion_filtro_pais_c2 (country = "Guatemala",anio_inicio_2  = 1990,anio_final_2 = 2014) %>%
 kable(caption = "Datos de Guatemala 1990-2014",
 digits = 1,align = "l") %>%
 kable_styling(bootstrap_options = "striped",
 full_width = TRUE)

Datos de Guatemala 1990-2014

	country	isocode	year	currency	rgdpe	rgdpo	pop	emp	avh	hc	ccon	cda	cgdpe	cgdpo	ck	ctfp	cwtfp	rgdpna	rconna	rdana	rkna	rtfpna	rwtfpna	labsh	delta	xr	pl_con	pl_da	pl_gdpo	i_cig	i_xm	i_xr	i_outlier	cor_exp	statcap	csh_c	csh_i	csh_g	csh_x	csh_m	csh_r	pl_c	pl_i	pl_g	pl_x	pl_m	pl_k
GTM-1990	Guatemala	GTM	1990	Quetzal	33234.6	34222.7	9.2	2.5	NA	1.5	32241.0	35134.4	33063.2	34293.3	45778.6	0.9	0.9	46215.4	41905.3	47471.4	126784.4	1.0	0.9	0.5	0.1	4.5	0.2	0.2	0.2	interpolated	benchmark	market	no	NA	NA	0.8	0.1	0.1	0.1	-0.1	0.0	0.2	0.4	0.2	0.5	0.5	0.3
GTM-1991	Guatemala	GTM	1991	Quetzal	35438.7	36470.8	9.4	2.6	NA	1.5	33555.4	37250.1	35158.6	36600.2	47208.3	0.9	0.9	47906.0	43432.1	50421.9	129355.2	1.0	0.9	0.5	0.1	5.0	0.2	0.2	0.2	interpolated	benchmark	market	no	NA	NA	0.8	0.1	0.1	0.1	-0.1	0.0	0.2	0.4	0.2	0.5	0.5	0.3
GTM-1992	Guatemala	GTM	1992	Quetzal	36326.2	37987.7	9.6	2.7	NA	1.5	35497.8	40458.9	35981.5	37812.5	49587.2	0.9	0.9	50223.9	45647.4	54848.9	133586.8	1.0	1.0	0.5	0.1	5.2	0.2	0.3	0.2	interpolated	benchmark	market	no	NA	NA	0.8	0.1	0.1	0.1	-0.1	0.0	0.2	0.4	0.2	0.5	0.5	0.4
GTM-1993	Guatemala	GTM	1993	Quetzal	38583.3	40375.7	9.9	2.8	NA	1.5	37369.7	42216.4	38180.7	40147.5	53500.3	0.9	0.9	52196.8	47680.4	56266.1	140097.1	1.0	1.0	0.5	0.1	5.6	0.2	0.3	0.3	interpolated	benchmark	market	no	NA	NA	0.8	0.1	0.1	0.1	-0.1	0.0	0.3	0.4	0.2	0.5	0.5	0.3
GTM-1994	Guatemala	GTM	1994	Quetzal	41145.2	42164.7	10.1	3.0	NA	1.6	39555.8	44458.9	40625.7	42118.2	57302.1	0.8	0.9	54301.9	49909.4	58601.2	144104.8	1.0	0.9	0.5	0.1	5.8	0.3	0.3	0.3	interpolated	benchmark	market	no	NA	NA	0.8	0.1	0.1	0.1	-0.1	0.0	0.3	0.4	0.2	0.5	0.5	0.4
GTM-1995	Guatemala	GTM	1995	Quetzal	43889.6	45114.5	10.4	3.0	NA	1.6	42208.8	47068.0	43522.3	45290.4	62316.2	0.9	0.9	56981.1	52361.3	60906.5	150601.8	1.0	0.9	0.5	0.1	5.8	0.3	0.3	0.3	interpolated	benchmark	market	no	NA	NA	0.8	0.1	0.1	0.1	-0.1	0.0	0.3	0.4	0.2	0.5	0.5	0.3
GTM-1996	Guatemala	GTM	1996	Quetzal	45516.4	46279.2	10.6	3.1	NA	1.6	43993.9	48135.5	45269.6	46609.7	66182.5	0.8	0.9	58669.1	53711.6	60829.8	154488.9	1.0	0.9	0.5	0.1	6.0	0.3	0.3	0.3	interpolated	benchmark	market	no	NA	NA	0.9	0.1	0.1	0.1	-0.1	0.0	0.3	0.5	0.2	0.6	0.5	0.4
GTM-1997	Guatemala	GTM	1997	Quetzal	48241.9	48901.3	10.9	3.2	NA	1.6	46064.6	51158.2	47688.0	49022.4	72300.2	0.8	0.8	61235.1	55940.7	64595.6	163422.1	1.0	0.9	0.5	0.1	6.1	0.3	0.3	0.3	interpolated	benchmark	market	no	NA	NA	0.9	0.1	0.1	0.1	-0.2	0.0	0.3	0.5	0.3	0.5	0.5	0.3
GTM-1998	Guatemala	GTM	1998	Quetzal	51417.2	51953.6	11.1	3.3	NA	1.6	48666.8	55740.6	50502.8	52091.2	79881.7	0.8	0.8	64293.3	58718.5	70643.4	172925.6	0.9	1.0	0.5	0.1	6.4	0.3	0.3	0.3	interpolated	benchmark	market	no	NA	NA	0.8	0.1	0.1	0.1	-0.2	0.0	0.3	0.5	0.3	0.5	0.5	0.4
GTM-1999	Guatemala	GTM	1999	Quetzal	53551.0	54882.2	11.4	3.4	NA	1.6	51127.0	58298.1	52587.8	54994.9	89127.0	0.8	0.8	66766.6	61015.4	72668.6	185427.2	0.9	0.9	0.5	0.1	7.4	0.3	0.3	0.3	interpolated	benchmark	market	no	NA	47.8	0.8	0.1	0.1	0.1	-0.2	0.0	0.3	0.4	0.3	0.5	0.5	0.3
GTM-2000	Guatemala	GTM	2000	Quetzal	56102.1	57968.2	11.7	3.6	NA	1.7	53538.4	61430.3	55067.0	57636.4	96989.8	0.7	0.7	69175.8	63408.1	75548.2	192628.2	0.9	0.9	0.5	0.1	7.8	0.3	0.3	0.3	interpolated	benchmark	market	no	NA	NA	0.8	0.1	0.1	0.1	-0.2	0.0	0.3	0.4	0.3	0.5	0.5	0.3
GTM-2001	Guatemala	GTM	2001	Quetzal	58489.1	61418.7	12.0	3.7	NA	1.6	56344.4	65172.1	57608.4	61010.9	103967.5	0.7	0.8	70788.7	65909.3	78846.1	198709.3	0.9	0.9	0.5	0.1	7.9	0.3	0.3	0.3	interpolated	benchmark	market	no	NA	NA	0.8	0.1	0.1	0.1	-0.2	0.0	0.3	0.4	0.3	0.5	0.5	0.4
GTM-2002	Guatemala	GTM	2002	Quetzal	61456.7	63811.9	12.3	3.9	NA	1.6	58545.0	68691.8	60556.7	63553.1	112948.9	0.7	0.8	73525.9	67883.9	81973.3	205983.8	0.9	0.9	0.5	0.1	7.8	0.3	0.3	0.3	interpolated	benchmark	market	no	NA	NA	0.8	0.2	0.1	0.1	-0.2	0.1	0.3	0.4	0.4	0.5	0.5	0.4
GTM-2003	Guatemala	GTM	2003	Quetzal	63583.8	66275.4	12.6	4.0	NA	1.6	61206.7	71559.9	62545.6	66160.8	122840.9	0.7	0.7	75386.6	70127.8	84049.5	212495.2	0.9	0.9	0.5	0.1	7.9	0.3	0.4	0.3	interpolated	benchmark	market	no	NA	NA	0.8	0.2	0.1	0.1	-0.2	0.0	0.3	0.4	0.4	0.5	0.5	0.4
GTM-2004	Guatemala	GTM	2004	Quetzal	66131.6	69108.5	12.9	4.0	NA	1.6	63706.6	74806.2	64977.1	69019.6	136110.9	0.7	0.7	77762.9	72080.1	86489.9	218599.4	0.9	1.0	0.4	0.1	7.9	0.4	0.4	0.3	interpolated	benchmark	market	no	NA	81.1	0.8	0.2	0.1	0.1	-0.2	0.1	0.4	0.5	0.4	0.5	0.5	0.4
GTM-2005	Guatemala	GTM	2005	Quetzal	68825.3	72399.2	13.2	4.2	NA	1.6	68320.2	79756.3	68791.5	72216.7	153376.9	0.7	0.7	80298.1	74991.0	89195.8	225095.9	0.9	1.0	0.4	0.1	7.6	0.4	0.4	0.4	interpolated	benchmark	market	no	NA	78.9	0.9	0.2	0.1	0.1	-0.3	0.0	0.4	0.5	0.4	0.6	0.5	0.4
GTM-2006	Guatemala	GTM	2006	Quetzal	73486.2	76669.0	13.5	4.5	NA	1.6	72078.9	85189.2	72839.5	76602.5	173933.1	0.7	0.7	84617.9	78573.3	94445.4	234027.8	0.9	1.0	0.4	0.0	7.6	0.4	0.4	0.4	interpolated	benchmark	market	no	NA	80.0	0.9	0.2	0.1	0.1	-0.2	0.0	0.4	0.5	0.4	0.6	0.6	0.4
GTM-2007	Guatemala	GTM	2007	Quetzal	79439.3	82025.2	13.8	4.5	NA	1.7	77205.1	91696.3	78528.7	82105.0	192681.0	0.7	0.7	89952.3	83017.8	100097.3	243391.2	1.0	1.0	0.4	0.0	7.7	0.4	0.4	0.4	interpolated	benchmark	market	no	NA	78.9	0.9	0.2	0.1	0.1	-0.3	0.0	0.4	0.5	0.4	0.6	0.6	0.4
GTM-2008	Guatemala	GTM	2008	Quetzal	83265.5	85980.3	14.1	4.5	NA	1.7	82892.9	95164.7	82976.3	85649.1	209983.8	0.7	0.7	92903.7	87139.7	100861.8	251030.0	1.0	1.0	0.4	0.0	7.6	0.5	0.5	0.5	interpolated	benchmark	market	no	NA	82.2	0.9	0.1	0.1	0.1	-0.3	0.0	0.5	0.5	0.5	0.7	0.6	0.4
GTM-2009	Guatemala	GTM	2009	Quetzal	87864.5	88414.6	14.4	4.5	NA	1.7	84656.9	95068.2	87094.7	88634.6	223994.4	0.7	0.7	93392.6	88072.6	99219.4	255899.8	1.0	0.9	0.4	0.0	8.2	0.4	0.4	0.4	interpolated	benchmark	market	no	NA	85.6	0.9	0.1	0.1	0.1	-0.2	0.0	0.4	0.5	0.4	0.7	0.6	0.4
GTM-2010	Guatemala	GTM	2010	Quetzal	92085.6	93170.7	14.7	4.3	NA	1.8	89748.7	101272.5	91646.2	93270.4	241053.6	0.7	0.7	96072.4	91514.5	103506.6	260478.3	1.0	1.0	0.4	0.0	8.1	0.4	0.5	0.4	interpolated	benchmark	market	no	NA	85.6	0.9	0.1	0.1	0.1	-0.2	0.0	0.4	0.5	0.4	0.7	0.6	0.4
GTM-2011	Guatemala	GTM	2011	Quetzal	98496.6	100070.9	15.0	4.5	NA	1.8	94919.2	109068.4	98496.6	100070.9	266095.2	0.7	0.7	100070.9	94919.2	109068.4	266095.2	1.0	1.0	0.4	0.0	7.8	0.5	0.5	0.5	benchmark	benchmark	market	no	0.6	83.3	0.8	0.1	0.1	0.1	-0.3	0.0	0.5	0.5	0.5	0.7	0.6	0.4
GTM-2012	Guatemala	GTM	2012	Quetzal	101200.2	102466.4	15.4	5.1	NA	1.8	98274.9	112493.7	101122.4	101964.9	272282.8	0.7	0.7	103043.0	98167.0	112555.0	272057.2	1.0	1.0	0.4	0.0	7.8	0.5	0.5	0.5	extrapolated	benchmark	market	no	NA	80.0	0.9	0.1	0.1	0.1	-0.3	0.0	0.5	0.5	0.5	0.7	0.6	0.4
GTM-2013	Guatemala	GTM	2013	Quetzal	104637.7	105246.7	15.7	4.9	NA	1.8	102153.3	115864.6	104280.2	104663.1	281013.8	0.7	0.7	106852.9	101996.6	116153.3	277956.6	1.0	1.0	0.4	0.0	7.9	0.5	0.5	0.5	extrapolated	benchmark	market	no	NA	76.7	0.9	0.1	0.1	0.1	-0.3	0.0	0.5	0.6	0.5	0.7	0.6	0.4
GTM-2014	Guatemala	GTM	2014	Quetzal	109715.6	110703.2	16.0	5.0	NA	1.8	106532.5	120539.6	109468.7	110100.0	292397.5	0.7	0.7	111393.9	106132.7	120700.0	284343.5	1.0	1.0	0.4	0.0	7.7	0.5	0.5	0.5	extrapolated	benchmark	market	no	NA	68.9	0.9	0.1	0.1	0.1	-0.3	0.0	0.5	0.6	0.5	0.7	0.6	0.4

2- Construya una función que le permita elegir todas las variables de la categoría “Labor detail”, muestre su uso para los datos de Argentina

library(dplyr)
library(kableExtra)
funcion_variable_labor_detail_c2 <- function(country,anio_inicio_3,anio_final_3) {
  pwt9.0 %>% filter(country==!!country,year>=anio_inicio_3,year<=anio_final_3) %>%
    select(country,year,emp, avh, hc, labsh)-> pais_periodo_4
  pais_periodo_4
}
funcion_variable_labor_detail_c2(country = "Argentina",anio_inicio_3  = 1950,anio_final_3 = 2014) %>%
 kable(caption = "Probando Función consulta Trade detail, ARG 1990-2014",
 digits = 1,align = "l") %>%
 kable_styling(bootstrap_options = "striped",
 full_width = TRUE)

Probando Función consulta Trade detail, ARG 1990-2014

	country	year	emp	avh	hc	labsh
ARG-1950	Argentina	1950	6.5	2034.0	1.8	0.5
ARG-1951	Argentina	1951	6.7	2037.9	1.8	0.5
ARG-1952	Argentina	1952	6.8	2041.7	1.8	0.5
ARG-1953	Argentina	1953	6.9	2045.6	1.9	0.5
ARG-1954	Argentina	1954	7.0	2049.5	1.9	0.5
ARG-1955	Argentina	1955	7.1	2053.4	1.9	0.5
ARG-1956	Argentina	1956	7.2	2057.3	1.9	0.5
ARG-1957	Argentina	1957	7.3	2061.2	1.9	0.5
ARG-1958	Argentina	1958	7.4	2065.1	1.9	0.5
ARG-1959	Argentina	1959	7.5	2069.1	1.9	0.5
ARG-1960	Argentina	1960	7.6	2073.0	2.0	0.5
ARG-1961	Argentina	1961	7.7	2066.2	2.0	0.5
ARG-1962	Argentina	1962	7.8	2059.4	2.0	0.5
ARG-1963	Argentina	1963	7.9	2052.7	2.0	0.5
ARG-1964	Argentina	1964	8.0	2045.9	2.0	0.5
ARG-1965	Argentina	1965	8.1	2039.2	2.0	0.5
ARG-1966	Argentina	1966	8.2	2032.5	2.0	0.5
ARG-1967	Argentina	1967	8.3	2025.9	2.0	0.5
ARG-1968	Argentina	1968	8.4	2019.2	2.0	0.5
ARG-1969	Argentina	1969	8.5	2012.6	2.1	0.5
ARG-1970	Argentina	1970	8.6	2006.0	2.1	0.5
ARG-1971	Argentina	1971	8.6	2002.7	2.1	0.5
ARG-1972	Argentina	1972	8.7	1999.3	2.1	0.5
ARG-1973	Argentina	1973	8.8	1996.0	2.1	0.5
ARG-1974	Argentina	1974	9.1	1992.8	2.2	0.5
ARG-1975	Argentina	1975	9.2	1989.7	2.2	0.5
ARG-1976	Argentina	1976	9.2	1986.5	2.2	0.5
ARG-1977	Argentina	1977	9.4	1983.4	2.2	0.5
ARG-1978	Argentina	1978	9.5	1980.3	2.2	0.5
ARG-1979	Argentina	1979	9.6	1977.1	2.2	0.5
ARG-1980	Argentina	1980	9.6	1974.0	2.3	0.5
ARG-1981	Argentina	1981	9.7	1961.2	2.3	0.5
ARG-1982	Argentina	1982	9.8	1948.5	2.3	0.5
ARG-1983	Argentina	1983	10.1	1935.9	2.4	0.5
ARG-1984	Argentina	1984	10.3	1923.4	2.4	0.5
ARG-1985	Argentina	1985	10.4	1911.0	2.4	0.5
ARG-1986	Argentina	1986	10.7	1898.6	2.4	0.5
ARG-1987	Argentina	1987	11.0	1886.3	2.5	0.5
ARG-1988	Argentina	1988	11.2	1874.1	2.5	0.5
ARG-1989	Argentina	1989	11.3	1862.0	2.5	0.5
ARG-1990	Argentina	1990	11.6	1850.0	2.5	0.5
ARG-1991	Argentina	1991	12.0	1838.0	2.6	0.5
ARG-1992	Argentina	1992	12.1	1826.0	2.6	0.5
ARG-1993	Argentina	1993	12.1	1850.3	2.6	0.5
ARG-1994	Argentina	1994	12.1	1875.0	2.6	0.5
ARG-1995	Argentina	1995	11.5	1897.2	2.6	0.5
ARG-1996	Argentina	1996	11.8	1846.1	2.6	0.4
ARG-1997	Argentina	1997	12.4	1917.3	2.6	0.4
ARG-1998	Argentina	1998	12.9	1903.0	2.6	0.4
ARG-1999	Argentina	1999	13.0	1893.2	2.6	0.5
ARG-2000	Argentina	2000	13.1	1861.0	2.7	0.5
ARG-2001	Argentina	2001	13.0	1803.4	2.7	0.5
ARG-2002	Argentina	2002	13.0	1610.6	2.7	0.4
ARG-2003	Argentina	2003	13.7	1719.4	2.7	0.4
ARG-2004	Argentina	2004	14.7	1739.7	2.8	0.4
ARG-2005	Argentina	2005	15.3	1755.3	2.8	0.4
ARG-2006	Argentina	2006	15.9	1809.4	2.8	0.4
ARG-2007	Argentina	2007	16.4	1816.9	2.8	0.4
ARG-2008	Argentina	2008	16.8	1835.9	2.8	0.4
ARG-2009	Argentina	2009	17.0	1736.9	2.8	0.4
ARG-2010	Argentina	2010	17.5	1728.7	2.8	0.4
ARG-2011	Argentina	2011	17.9	1762.3	2.9	0.4
ARG-2012	Argentina	2012	18.1	1789.0	2.9	0.4
ARG-2013	Argentina	2013	18.3	1776.7	2.9	0.4
ARG-2014	Argentina	2014	18.1	1776.7	2.9	0.4

3- Use las funciones creadas en 1 y 2, para generar 2 dataframes, que muestren los datos de “EE.UU” y “Canadá” para el periodo 2000-2014

dataframe_clave2<-funcion_filtro_pais_c2(country = c("United States of America","Canada"),anio_inicio_2 = 2000,anio_final_2 = 2014)
print(dataframe_clave2)

##                           country isocode year        currency    rgdpe
## CAN-2001                   Canada     CAN 2001 Canadian Dollar  1166188
## CAN-2003                   Canada     CAN 2003 Canadian Dollar  1211094
## CAN-2005                   Canada     CAN 2005 Canadian Dollar  1311424
## CAN-2007                   Canada     CAN 2007 Canadian Dollar  1376870
## CAN-2009                   Canada     CAN 2009 Canadian Dollar  1310934
## CAN-2011                   Canada     CAN 2011 Canadian Dollar  1423920
## CAN-2013                   Canada     CAN 2013 Canadian Dollar  1478439
## USA-2000 United States of America     USA 2000       US Dollar 13222419
## USA-2002 United States of America     USA 2002       US Dollar 13591523
## USA-2004 United States of America     USA 2004       US Dollar 14499944
## USA-2006 United States of America     USA 2006       US Dollar 15353601
## USA-2008 United States of America     USA 2008       US Dollar 15357469
## USA-2010 United States of America     USA 2010       US Dollar 15368666
## USA-2012 United States of America     USA 2012       US Dollar 15976742
## USA-2014 United States of America     USA 2014       US Dollar 16704698
##             rgdpo       pop       emp      avh       hc       ccon      cda
## CAN-2001  1119308  30.99134  15.05903 1767.990 3.518916   814203.9  1079932
## CAN-2003  1184269  31.59659  15.84749 1732.136 3.548723   858441.9  1148489
## CAN-2005  1323181  32.25633  16.43793 1739.182 3.578782   918976.9  1263380
## CAN-2007  1384391  32.98228  17.26695 1724.689 3.609095   969776.7  1342214
## CAN-2009  1304883  33.74656  17.43560 1678.515 3.639666  1000717.9  1325223
## CAN-2011  1455816  34.49990  18.07691 1683.574 3.662325  1045868.8  1440603
## CAN-2013  1493624  35.23061  18.66565 1682.736 3.676923  1086339.8  1488701
## USA-2000 13031820 282.89574 139.29607 1848.147 3.578583  9977582.0 13511612
## USA-2002 13309916 288.47085 139.08432 1805.477 3.598119 10524779.0 14027745
## USA-2004 14204685 293.53089 141.63098 1783.413 3.617761 11251801.0 15090846
## USA-2006 15083465 298.86052 146.61525 1778.528 3.642329 12126527.0 16170304
## USA-2008 15305872 304.47314 147.52623 1761.316 3.671921 12569281.0 16125585
## USA-2010 15250698 309.87617 141.34911 1738.001 3.701753 12764841.0 15842214
## USA-2012 15899255 314.79946 144.86284 1753.699 3.712276 13206454.0 16505245
## USA-2014 16598099 319.44863 148.46339 1764.597 3.722829 13685949.0 17113208
##             cgdpe    cgdpo       ck      ctfp     cwtfp   rgdpna     rconna
## CAN-2001  1145022  1144414  3268334 0.9022754 0.8153173  1190649   782785.5
## CAN-2003  1194611  1200543  3349291 0.8915871 0.8093318  1247575   832796.8
## CAN-2005  1315081  1326233  3865556 0.9038564 0.7981808  1327435   882079.1
## CAN-2007  1370408  1395106  4445640 0.8834894 0.8020070  1389595   950916.3
## CAN-2009  1306457  1323073  4794360 0.8118237 0.7897093  1367808   994270.1
## CAN-2011  1423920  1455816  5427466 0.8070218 0.7662106  1455816  1045868.8
## CAN-2013  1465085  1472069  5828469 0.7754062 0.7574083  1513537  1084256.5
## USA-2000 13035321 12983206 35997032 1.0000000 1.0000000 12975535 10500206.0
## USA-2002 13503168 13339370 38467564 1.0000000 1.0000000 13336194 11088529.0
## USA-2004 14366189 14232334 42071616 1.0000000 1.0000000 14229557 11796878.0
## USA-2006 15318001 15099868 47891040 1.0000000 1.0000000 15097712 12476968.0
## USA-2008 15370500 15321926 50006724 1.0000000 1.0000000 15321422 12759836.0
## USA-2010 15317448 15273702 48876336 1.0000000 1.0000000 15273331 12883714.0
## USA-2012 15946878 15863845 50020716 1.0000000 1.0000000 15863049 13182059.0
## USA-2014 16605887 16490883 52849892 1.0000000 1.0000000 16490192 13585164.0
##             rdana     rkna    rtfpna   rwtfpna     labsh      delta        xr
## CAN-2001  1041029  3905941 1.0337603 0.9134005 0.6171623 0.04350585 1.5487608
## CAN-2003  1119539  4151862 1.0330168 0.9367892 0.6124471 0.04180438 1.4010517
## CAN-2005  1221829  4462552 1.0369463 0.9645296 0.5987505 0.04020973 1.2117633
## CAN-2007  1319552  4812567 1.0226208 0.9813300 0.6059821 0.03873762 1.0740992
## CAN-2009  1323141  5106391 0.9890912 0.9668959 0.6315947 0.03881708 1.1431006
## CAN-2011  1440603  5427466 1.0000000 1.0000000 0.6074459 0.03708802 0.9895307
## CAN-2013  1500049  5779532 0.9928653 0.9944088 0.6191180 0.03645137 1.0297966
## USA-2000 13647352 38439588 0.9205835 0.9289908 0.6426795 0.05212035 1.0000000
## USA-2002 14123900 40679832 0.9388351 0.9539754 0.6347357 0.05012728 1.0000000
## USA-2004 15181932 43024076 0.9741488 0.9972088 0.6222099 0.04774661 1.0000000
## USA-2006 16121374 45671956 0.9863822 1.0105580 0.6123036 0.04556167 1.0000000
## USA-2008 16086510 47779436 0.9808996 0.9881262 0.6150548 0.04627780 1.0000000
## USA-2010 15924426 48728140 0.9990609 0.9994178 0.5952319 0.04710827 1.0000000
## USA-2012 16509182 49960600 1.0051460 1.0036752 0.6020187 0.04788478 1.0000000
## USA-2014 17137356 51190644 1.0141082 1.0111778 0.6035975 0.04704589 1.0000000
##             pl_con     pl_da   pl_gdpo        i_cig      i_xm   i_xr i_outlier
## CAN-2001 0.6702421 0.6399313 0.6402714 interpolated benchmark market        no
## CAN-2003 0.7807368 0.7431563 0.7394839 interpolated benchmark market        no
## CAN-2005 0.9279599 0.8852534 0.8778094    benchmark benchmark market        no
## CAN-2007 1.1123220 1.0638244 1.0449910 interpolated benchmark market        no
## CAN-2009 1.0911957 1.0492800 1.0361022 interpolated benchmark market        no
## CAN-2011 1.3175685 1.2562085 1.2286866    benchmark benchmark market        no
## CAN-2013 1.3056631 1.2551931 1.2492380 extrapolated benchmark market        no
## USA-2000 0.8255066 0.7889932 0.7921603 interpolated benchmark market        no
## USA-2002 0.8584893 0.8129588 0.8229414    benchmark benchmark market        no
## USA-2004 0.9002079 0.8544319 0.8624678 interpolated benchmark market        no
## USA-2006 0.9395798 0.9045495 0.9176166 interpolated benchmark market        no
## USA-2008 0.9851168 0.9575869 0.9606227 interpolated benchmark market        no
## USA-2010 0.9968326 0.9769499 0.9797481 interpolated benchmark market        no
## USA-2012 1.0294040 1.0130669 1.0183694 extrapolated benchmark market        no
## USA-2014 1.0537966 1.0446941 1.0519795 extrapolated benchmark market        no
##            cor_exp statcap     csh_c     csh_i      csh_g      csh_x      csh_m
## CAN-2001        NA      NA 0.5601038 0.2321958 0.15135552 0.41777286 -0.3644541
## CAN-2003        NA      NA 0.5621071 0.2415964 0.15293744 0.39027315 -0.3496419
## CAN-2005 0.9038276      NA 0.5438991 0.2596853 0.14902379 0.43287170 -0.3851879
## CAN-2007        NA      NA 0.5394937 0.2669595 0.15563411 0.44280696 -0.3985552
## CAN-2009        NA      NA 0.5724548 0.2452664 0.18390381 0.34533143 -0.3370062
## CAN-2011 0.8238315      NA 0.5405646 0.2711428 0.17784286 0.43870276 -0.4166212
## CAN-2013        NA      NA 0.5595505 0.2733303 0.17841771 0.42063153 -0.4186161
## USA-2000        NA      NA 0.6758358 0.2722001 0.09266327 0.10603466 -0.1566473
## USA-2002        NA      NA 0.6889258 0.2626036 0.10007539 0.09348762 -0.1526167
## USA-2004        NA      NA 0.6870325 0.2697411 0.10354772 0.09122263 -0.1587287
## USA-2006        NA      NA 0.6949668 0.2678021 0.10812150 0.10488261 -0.1837855
## USA-2008        NA      NA 0.7019295 0.2321056 0.11841653 0.11299946 -0.1750899
## USA-2010        NA      NA 0.7068287 0.2014818 0.12891109 0.11498131 -0.1603202
## USA-2012        NA      NA 0.7113655 0.2079439 0.12112205 0.12747377 -0.1780486
## USA-2014        NA      NA 0.7167840 0.2078275 0.11312606 0.12769014 -0.1767433
##                  csh_r      pl_c      pl_i      pl_g      pl_x      pl_m
## CAN-2001  0.0030260538 0.6292517 0.5470572 0.8219304 0.5460286 0.5313601
## CAN-2003  0.0027277917 0.7315946 0.6319304 0.9613546 0.5810179 0.5726507
## CAN-2005 -0.0002920294 0.8729587 0.7712987 1.1287004 0.6280424 0.6155325
## CAN-2007 -0.0063390261 1.0543412 0.9375428 1.3133082 0.6796820 0.6845841
## CAN-2009 -0.0099502383 1.0351254 0.9200191 1.2657314 0.6898180 0.7204297
## CAN-2011 -0.0116318641 1.2595756 1.0936318 1.4938417 0.7052622 0.7428895
## CAN-2013 -0.0133138811 1.2401137 1.1189287 1.5112380 0.7374130 0.7493351
## USA-2000  0.0099134836 0.7741043 0.6859053 1.2004077 0.5668258 0.6185908
## USA-2002  0.0075242864 0.8035018 0.6761612 1.2370269 0.5558824 0.5905658
## USA-2004  0.0071848887 0.8447491 0.7202677 1.2681735 0.6299770 0.6751730
## USA-2006  0.0080124773 0.8866088 0.7995001 1.2800587 0.6548091 0.6914976
## USA-2008  0.0096388310 0.9310760 0.8602863 1.3054508 0.7507930 0.8069550
## USA-2010  0.0081172762 0.9450076 0.8944773 1.2809926 0.7277685 0.7809259
## USA-2012  0.0101433368 0.9792322 0.9476624 1.3240701 0.7639757 0.8052509
## USA-2014  0.0113156438 1.0038527 1.0083452 1.3702492 0.7692084 0.8049124
##               pl_k
## CAN-2001 0.6292847
## CAN-2003 0.7568532
## CAN-2005 0.8875628
## CAN-2007 1.0519462
## CAN-2009 1.0221647
## CAN-2011 1.1579119
## CAN-2013 1.1488672
## USA-2000 0.7926286
## USA-2002 0.8231374
## USA-2004 0.8626361
## USA-2006 0.9177476
## USA-2008 0.9606543
## USA-2010 0.9797719
## USA-2012 1.0184206
## USA-2014 1.0520236

dataframe_2<-funcion_variable_labor_detail_c2(country = c("United States of America","Canada"),anio_inicio_3 = 2000,anio_final_3 = 2014)
print(dataframe_2)

##                           country year       emp      avh       hc     labsh
## CAN-2001                   Canada 2001  15.05903 1767.990 3.518916 0.6171623
## CAN-2003                   Canada 2003  15.84749 1732.136 3.548723 0.6124471
## CAN-2005                   Canada 2005  16.43793 1739.182 3.578782 0.5987505
## CAN-2007                   Canada 2007  17.26695 1724.689 3.609095 0.6059821
## CAN-2009                   Canada 2009  17.43560 1678.515 3.639666 0.6315947
## CAN-2011                   Canada 2011  18.07691 1683.574 3.662325 0.6074459
## CAN-2013                   Canada 2013  18.66565 1682.736 3.676923 0.6191180
## USA-2000 United States of America 2000 139.29607 1848.147 3.578583 0.6426795
## USA-2002 United States of America 2002 139.08432 1805.477 3.598119 0.6347357
## USA-2004 United States of America 2004 141.63098 1783.413 3.617761 0.6222099
## USA-2006 United States of America 2006 146.61525 1778.528 3.642329 0.6123036
## USA-2008 United States of America 2008 147.52623 1761.316 3.671921 0.6150548
## USA-2010 United States of America 2010 141.34911 1738.001 3.701753 0.5952319
## USA-2012 United States of America 2012 144.86284 1753.699 3.712276 0.6020187
## USA-2014 United States of America 2014 148.46339 1764.597 3.722829 0.6035975

Clave 3

1- Construya una función que le permita elegir el país y filtrar para un periodo(inicio,final), muestre su uso filtrando los datos para Honduras, en el periodo de 1990-2014.

library(dplyr)
library(kableExtra)
options(scipen = 999999)
funcion_filtro_pais_c3 <- function(country,anio_inicio_3,anio_final_3) {
  pwt9.0 %>% filter(country==!!country,
year>=anio_inicio_3,year<=anio_final_3) -> pais_periodo_5
  pais_periodo_5
}
funcion_filtro_pais_c3(country = "Honduras",anio_inicio_3  = 1990,anio_final_3 = 2014) %>%
 kable(caption = "Datos de Honduras 1990-2014",
 digits = 1,align = "l") %>%
 kable_styling(bootstrap_options = "striped",
 full_width = TRUE)

Datos de Honduras 1990-2014

	country	isocode	year	currency	rgdpe	rgdpo	pop	emp	avh	hc	ccon	cda	cgdpe	cgdpo	ck	ctfp	cwtfp	rgdpna	rconna	rdana	rkna	rtfpna	rwtfpna	labsh	delta	xr	pl_con	pl_da	pl_gdpo	i_cig	i_xm	i_xr	i_outlier	cor_exp	statcap	csh_c	csh_i	csh_g	csh_x	csh_m	csh_r	pl_c	pl_i	pl_g	pl_x	pl_m	pl_k
HND-1990	Honduras	HND	1990	Lempira	13869.7	14480.0	4.9	1.2	NA	1.8	12349.6	14292.9	14019.5	14777.8	24019.2	0.6	0.6	15670.5	14036.9	16844.1	46727.6	1.2	1.2	0.6	0.0	4.1	0.2	0.3	0.2	interpolated	benchmark	market	no	NA	NA	0.7	0.1	0.1	0.1	-0.1	0.1	0.2	0.4	0.3	0.5	0.5	0.4
HND-1991	Honduras	HND	1991	Lempira	14668.8	15217.2	5.0	1.5	NA	1.8	12721.9	15095.5	14801.8	15593.7	24835.8	0.6	0.5	16180.1	14378.0	17783.9	48069.2	1.1	1.0	0.6	0.0	5.3	0.2	0.2	0.2	interpolated	benchmark	market	no	NA	NA	0.7	0.2	0.1	0.1	-0.1	0.1	0.2	0.4	0.3	0.5	0.5	0.4
HND-1992	Honduras	HND	1992	Lempira	15327.7	15702.4	5.2	1.7	NA	1.8	13162.2	15913.1	15452.5	15956.8	26166.6	0.5	0.5	17090.1	14913.3	18787.8	50292.8	1.1	1.0	0.6	0.0	5.5	0.2	0.3	0.3	interpolated	benchmark	market	no	NA	NA	0.7	0.2	0.1	0.1	-0.1	0.0	0.2	0.4	0.3	0.5	0.5	0.4
HND-1993	Honduras	HND	1993	Lempira	15933.6	17007.8	5.3	1.7	NA	1.8	13556.2	17219.0	16058.7	17298.6	28826.0	0.5	0.5	18154.8	15235.9	20400.8	53997.6	1.1	1.1	0.6	0.1	6.5	0.2	0.3	0.2	interpolated	benchmark	market	no	NA	NA	0.7	0.2	0.1	0.1	-0.2	0.1	0.2	0.4	0.3	0.5	0.5	0.4
HND-1994	Honduras	HND	1994	Lempira	16221.7	17431.8	5.5	1.8	NA	1.8	13626.8	17519.9	16247.2	17766.1	31566.0	0.5	0.5	17918.2	15181.7	20793.2	57416.0	1.0	1.0	0.6	0.1	8.4	0.2	0.3	0.2	interpolated	benchmark	market	no	NA	NA	0.7	0.2	0.1	0.1	-0.2	0.1	0.2	0.4	0.3	0.5	0.5	0.3
HND-1995	Honduras	HND	1995	Lempira	17476.4	19391.9	5.6	1.8	NA	1.8	13971.4	17967.3	17503.1	19796.2	33959.8	0.5	0.5	18649.3	15343.4	21133.8	59647.0	1.0	1.0	0.6	0.1	9.5	0.2	0.3	0.2	interpolated	benchmark	market	no	NA	NA	0.6	0.2	0.1	0.1	-0.2	0.2	0.2	0.3	0.4	0.5	0.5	0.4
HND-1996	Honduras	HND	1996	Lempira	17991.7	18534.6	5.7	2.0	NA	1.8	14862.3	18612.0	17993.6	18919.2	36097.2	0.5	0.5	19316.6	16146.4	21565.4	62041.0	1.0	1.0	0.6	0.1	11.7	0.2	0.3	0.3	interpolated	benchmark	market	no	NA	NA	0.7	0.2	0.1	0.1	-0.2	0.1	0.2	0.4	0.4	0.6	0.5	0.4
HND-1997	Honduras	HND	1997	Lempira	18783.4	19283.0	5.9	2.1	NA	1.8	15261.0	19375.8	18662.3	19602.3	38920.0	0.5	0.4	20281.2	16564.7	22439.0	65095.4	1.0	0.9	0.6	0.1	13.0	0.3	0.3	0.3	interpolated	benchmark	market	no	NA	NA	0.7	0.2	0.1	0.1	-0.2	0.1	0.3	0.4	0.4	0.5	0.5	0.4
HND-1998	Honduras	HND	1998	Lempira	19437.3	19877.3	6.0	2.1	NA	1.9	16084.1	20327.3	19169.8	20236.4	42338.4	0.4	0.4	20869.7	17542.5	23514.3	68522.9	1.0	0.9	0.6	0.1	13.4	0.3	0.3	0.3	interpolated	benchmark	market	no	NA	NA	0.7	0.2	0.1	0.2	-0.3	0.1	0.3	0.4	0.5	0.5	0.5	0.4
HND-1999	Honduras	HND	1999	Lempira	18722.7	19555.4	6.1	2.3	NA	1.9	16175.8	20880.7	18457.6	19883.2	46072.1	0.4	0.4	20475.4	17648.5	24128.7	72088.2	0.9	0.9	0.6	0.1	14.2	0.3	0.4	0.3	interpolated	benchmark	market	no	NA	60.6	0.7	0.2	0.1	0.1	-0.3	0.1	0.3	0.4	0.5	0.5	0.5	0.4
HND-2000	Honduras	HND	2000	Lempira	20014.3	21004.3	6.2	2.3	NA	1.9	17440.5	22230.8	19769.9	21097.9	49552.6	0.4	0.4	21652.3	19076.1	25351.3	74802.0	0.9	0.9	0.6	0.1	14.8	0.3	0.4	0.3	interpolated	benchmark	market	no	NA	NA	0.7	0.2	0.1	0.1	-0.2	0.1	0.3	0.4	0.5	0.5	0.5	0.4
HND-2001	Honduras	HND	2001	Lempira	20637.6	21337.6	6.4	2.3	NA	1.9	18379.9	23177.1	20478.2	21473.4	52978.8	0.4	0.4	22242.0	19999.8	26028.0	77193.2	0.9	0.9	0.6	0.1	15.5	0.4	0.4	0.4	interpolated	benchmark	market	no	NA	NA	0.8	0.2	0.1	0.1	-0.3	0.0	0.3	0.4	0.5	0.4	0.5	0.4
HND-2002	Honduras	HND	2002	Lempira	21429.9	22322.8	6.5	2.3	NA	1.9	19132.1	23977.6	21306.5	22633.9	56023.2	0.4	0.4	23077.0	20740.8	26554.2	79013.1	1.0	1.0	0.6	0.1	16.4	0.4	0.4	0.3	interpolated	benchmark	market	no	NA	NA	0.8	0.2	0.1	0.1	-0.3	0.1	0.3	0.4	0.6	0.5	0.5	0.4
HND-2003	Honduras	HND	2003	Lempira	22293.7	23442.7	6.6	2.4	NA	1.9	20103.3	25232.9	22122.4	23866.7	59671.4	0.4	0.4	24126.3	21693.0	27731.2	81101.3	1.0	1.0	0.6	0.1	17.3	0.4	0.4	0.3	interpolated	benchmark	market	no	NA	NA	0.7	0.2	0.1	0.1	-0.3	0.1	0.3	0.4	0.5	0.5	0.5	0.4
HND-2004	Honduras	HND	2004	Lempira	23503.4	24886.9	6.8	2.4	NA	2.0	21223.1	27632.3	23295.6	25364.9	65749.5	0.4	0.4	25629.9	22787.2	30171.7	84672.6	1.0	1.0	0.6	0.1	18.2	0.4	0.4	0.3	interpolated	benchmark	market	no	NA	63.9	0.7	0.3	0.1	0.1	-0.3	0.1	0.3	0.4	0.6	0.5	0.5	0.4
HND-2005	Honduras	HND	2005	Lempira	24863.1	27339.3	6.9	2.5	NA	2.0	23171.7	29687.9	25057.7	27758.7	72955.4	0.4	0.4	27180.8	24338.4	31628.4	87856.1	1.0	1.0	0.6	0.1	18.8	0.4	0.4	0.4	interpolated	benchmark	market	no	NA	63.3	0.7	0.2	0.1	0.1	-0.3	0.1	0.4	0.4	0.5	0.5	0.5	0.4
HND-2006	Honduras	HND	2006	Lempira	26591.9	28317.3	7.0	2.6	NA	2.0	25053.5	32155.2	26569.6	28826.4	81215.1	0.4	0.4	28965.8	26253.9	34069.2	91934.2	1.0	1.0	0.6	0.1	18.9	0.4	0.4	0.4	interpolated	benchmark	market	no	NA	63.3	0.8	0.2	0.1	0.1	-0.3	0.1	0.4	0.4	0.6	0.6	0.6	0.4
HND-2007	Honduras	HND	2007	Lempira	28196.9	30212.6	7.1	2.8	NA	2.0	26953.7	35926.3	28055.9	30818.3	89601.1	0.4	0.4	30758.2	28137.4	37910.0	98000.6	1.0	1.1	0.6	0.1	18.9	0.4	0.4	0.4	interpolated	benchmark	market	no	NA	70.0	0.8	0.3	0.1	0.1	-0.3	0.1	0.4	0.5	0.6	0.6	0.6	0.4
HND-2008	Honduras	HND	2008	Lempira	28689.7	29158.4	7.3	2.8	NA	2.0	28240.2	38256.5	28743.0	29235.6	97798.8	0.4	0.4	32059.9	29045.7	39696.9	104314.8	1.1	1.1	0.6	0.1	18.9	0.5	0.5	0.5	interpolated	benchmark	market	no	NA	73.3	0.8	0.3	0.1	0.3	-0.5	-0.1	0.5	0.5	0.7	0.7	0.7	0.4
HND-2009	Honduras	HND	2009	Lempira	29242.9	29286.4	7.4	2.9	NA	2.0	28587.6	34253.8	29066.9	29677.8	100695.9	0.3	0.4	31280.2	29424.5	35252.2	105943.4	1.0	1.0	0.6	0.1	18.9	0.5	0.5	0.5	interpolated	benchmark	market	no	NA	77.8	0.8	0.2	0.1	0.1	-0.3	0.0	0.5	0.5	0.7	0.7	0.6	0.4
HND-2010	Honduras	HND	2010	Lempira	30846.4	31120.9	7.5	2.9	NA	2.1	29819.8	36243.6	30734.7	31326.9	104274.6	0.3	0.4	32447.4	30233.1	36788.3	107767.7	1.0	1.0	0.6	0.1	18.9	0.5	0.5	0.5	interpolated	benchmark	market	no	NA	77.8	0.8	0.2	0.1	0.1	-0.4	0.1	0.5	0.5	0.7	0.7	0.6	0.4
HND-2011	Honduras	HND	2011	Lempira	32806.5	33691.9	7.6	3.1	NA	2.1	31070.4	39269.9	32806.5	33691.9	110959.4	0.3	0.4	33691.9	31070.4	39269.9	110959.4	1.0	1.0	0.6	0.1	18.9	0.5	0.5	0.5	benchmark	benchmark	market	no	0.6	77.8	0.8	0.2	0.1	0.1	-0.4	0.1	0.5	0.6	0.7	0.7	0.6	0.5
HND-2012	Honduras	HND	2012	Lempira	33773.0	34602.0	7.7	3.2	NA	2.1	32356.3	40233.3	33701.1	34306.4	114260.5	0.3	0.4	35083.0	32295.1	40251.7	114391.2	1.0	1.0	0.6	0.1	19.5	0.5	0.5	0.5	extrapolated	benchmark	market	no	NA	76.0	0.8	0.2	0.1	0.2	-0.4	0.0	0.5	0.6	0.8	0.7	0.7	0.5
HND-2013	Honduras	HND	2013	Lempira	33759.9	33670.3	7.8	3.3	NA	2.2	33565.7	40386.9	33537.5	33307.6	118671.2	0.3	0.4	36062.3	33478.7	40477.3	117494.7	1.0	0.9	0.6	0.1	20.3	0.5	0.6	0.6	extrapolated	benchmark	market	no	NA	62.2	0.9	0.2	0.1	0.3	-0.4	-0.1	0.5	0.6	0.8	0.7	0.6	0.4
HND-2014	Honduras	HND	2014	Lempira	35219.2	34835.7	8.0	3.4	NA	2.2	34384.1	41614.7	35008.4	34377.6	123703.3	0.3	0.4	37174.9	34161.5	41649.4	120378.6	1.0	0.9	0.6	0.1	21.0	0.5	0.6	0.6	extrapolated	benchmark	market	no	NA	73.3	0.9	0.2	0.1	0.3	-0.5	-0.1	0.5	0.6	0.8	0.7	0.6	0.4

2- Construya una función que le permita elegir todas las variables de la categoría “Capital detail”, muestre su uso para los datos de Panamá.

funcion_variable_capital_detail_c3 <- function(country,anio_inicio_4,anio_final_4) {
  pwt9.0 %>% filter(country==!!country,year>=anio_inicio_4,year<=anio_final_4) %>%
    select(country,year,ck, rkna, pl_k)-> pais_periodo_6
  pais_periodo_6
}
funcion_variable_capital_detail_c3(country = "Panama",anio_inicio_4  = 1950,anio_final_4 = 2014) %>%
 kable(caption = "Probando Función consulta Trade detail, ARG 1990-2014",
 digits = 1,align = "l") %>%
 kable_styling(bootstrap_options = "striped",
 full_width = TRUE)

Probando Función consulta Trade detail, ARG 1990-2014

	country	year	ck	rkna	pl_k
PAN-1950	Panama	1950	3974.4	7910.7	0.2
PAN-1951	Panama	1951	4069.1	7852.9	0.2
PAN-1952	Panama	1952	4146.3	7819.0	0.2
PAN-1953	Panama	1953	4194.0	7919.3	0.2
PAN-1954	Panama	1954	4124.0	7955.6	0.2
PAN-1955	Panama	1955	4161.5	8047.9	0.2
PAN-1956	Panama	1956	4363.7	8225.0	0.2
PAN-1957	Panama	1957	4487.4	8409.0	0.2
PAN-1958	Panama	1958	4531.0	8648.3	0.2
PAN-1959	Panama	1959	4688.3	8946.8	0.2
PAN-1960	Panama	1960	4690.7	9182.7	0.2
PAN-1961	Panama	1961	4875.8	9531.8	0.2
PAN-1962	Panama	1962	5083.9	9964.5	0.2
PAN-1963	Panama	1963	5296.1	10468.6	0.2
PAN-1964	Panama	1964	5434.3	10876.9	0.2
PAN-1965	Panama	1965	5712.3	11372.3	0.2
PAN-1966	Panama	1966	6162.0	12153.6	0.2
PAN-1967	Panama	1967	6605.5	12955.6	0.2
PAN-1968	Panama	1968	7103.5	13884.0	0.2
PAN-1969	Panama	1969	7759.3	14962.7	0.2
PAN-1970	Panama	1970	8744.9	16607.6	0.2
PAN-1971	Panama	1971	9853.1	18485.3	0.2
PAN-1972	Panama	1972	11258.1	20871.1	0.2
PAN-1973	Panama	1973	12697.5	23114.2	0.2
PAN-1974	Panama	1974	14108.2	24912.7	0.3
PAN-1975	Panama	1975	15473.7	26847.1	0.3
PAN-1976	Panama	1976	16559.0	28760.0	0.3
PAN-1977	Panama	1977	17266.5	29532.2	0.3
PAN-1978	Panama	1978	18411.5	30826.6	0.4
PAN-1979	Panama	1979	19512.7	32049.5	0.4
PAN-1980	Panama	1980	20876.9	33797.9	0.4
PAN-1981	Panama	1981	22641.3	36217.0	0.4
PAN-1982	Panama	1982	24276.0	38632.2	0.4
PAN-1983	Panama	1983	24367.4	39796.4	0.5
PAN-1984	Panama	1984	24464.8	40627.0	0.4
PAN-1985	Panama	1985	24666.5	41321.0	0.5
PAN-1986	Panama	1986	25712.5	42623.7	0.5
PAN-1987	Panama	1987	26721.9	44186.4	0.5
PAN-1988	Panama	1988	26434.9	43668.6	0.4
PAN-1989	Panama	1989	25723.7	42711.3	0.5
PAN-1990	Panama	1990	25448.7	42280.0	0.5
PAN-1991	Panama	1991	25695.9	43114.4	0.5
PAN-1992	Panama	1992	26580.9	44983.6	0.5
PAN-1993	Panama	1993	28817.3	48241.7	0.5
PAN-1994	Panama	1994	31240.9	51560.6	0.5
PAN-1995	Panama	1995	34024.9	55079.7	0.5
PAN-1996	Panama	1996	36206.4	58254.4	0.5
PAN-1997	Panama	1997	39246.6	61684.6	0.5
PAN-1998	Panama	1998	43127.2	65850.3	0.5
PAN-1999	Panama	1999	47489.8	70507.2	0.5
PAN-2000	Panama	2000	51416.7	74266.6	0.5
PAN-2001	Panama	2001	53947.7	75946.8	0.4
PAN-2002	Panama	2002	56263.8	77322.8	0.4
PAN-2003	Panama	2003	60077.4	79968.2	0.4
PAN-2004	Panama	2004	65767.7	83185.1	0.4
PAN-2005	Panama	2005	73176.2	86754.7	0.4
PAN-2006	Panama	2006	81943.7	91417.5	0.4
PAN-2007	Panama	2007	92301.1	99499.9	0.5
PAN-2008	Panama	2008	103622.5	109266.6	0.5
PAN-2009	Panama	2009	112844.9	117965.0	0.5
PAN-2010	Panama	2010	124656.5	128348.8	0.5
PAN-2011	Panama	2011	142056.7	142056.7	0.6
PAN-2012	Panama	2012	158524.4	159050.1	0.6
PAN-2013	Panama	2013	179119.1	178155.9	0.5
PAN-2014	Panama	2014	201345.0	197037.3	0.5

3- Use las funciones creadas en 1 y 2, para generar 2 dataframes, que muestren los datos de “EE.UU” y “Reino Unido” para el periodo 1990-2000

dataframe3<-funcion_filtro_pais_c3(country = c("United States of America","United Kingdom"),anio_inicio_3 = 2000,anio_final_3 = 2014)
print(dataframe3)

##                           country isocode year       currency    rgdpe    rgdpo
## GBR-2000           United Kingdom     GBR 2000 Pound Sterling  2088803  2024305
## GBR-2002           United Kingdom     GBR 2002 Pound Sterling  2175498  2086833
## GBR-2004           United Kingdom     GBR 2004 Pound Sterling  2289329  2153446
## GBR-2006           United Kingdom     GBR 2006 Pound Sterling  2404281  2302793
## GBR-2008           United Kingdom     GBR 2008 Pound Sterling  2421008  2323823
## GBR-2010           United Kingdom     GBR 2010 Pound Sterling  2288598  2177450
## GBR-2012           United Kingdom     GBR 2012 Pound Sterling  2389794  2287097
## GBR-2014           United Kingdom     GBR 2014 Pound Sterling  2588791  2493279
## USA-2000 United States of America     USA 2000      US Dollar 13222419 13031820
## USA-2002 United States of America     USA 2002      US Dollar 13591523 13309916
## USA-2004 United States of America     USA 2004      US Dollar 14499944 14204685
## USA-2006 United States of America     USA 2006      US Dollar 15353601 15083465
## USA-2008 United States of America     USA 2008      US Dollar 15357469 15305872
## USA-2010 United States of America     USA 2010      US Dollar 15368666 15250698
## USA-2012 United States of America     USA 2012      US Dollar 15976742 15899255
## USA-2014 United States of America     USA 2014      US Dollar 16704698 16598099
##                pop       emp      avh       hc     ccon      cda    cgdpe
## GBR-2000  58.86700  27.31735 1699.107 3.509591  1650633  2054763  2015176
## GBR-2002  59.30123  27.76327 1681.323 3.547473  1776909  2177053  2115245
## GBR-2004  59.84623  28.35924 1654.646 3.585763  1869910  2295413  2232693
## GBR-2006  60.64885  29.00422 1666.594 3.624467  1953109  2437369  2376343
## GBR-2008  61.68962  29.60776 1647.057 3.663588  1999632  2486845  2413115
## GBR-2010  62.71668  29.35739 1643.919 3.703131  1872350  2342944  2279856
## GBR-2012  63.57377  29.89977 1657.981 3.718676  1931668  2432806  2384291
## GBR-2014  64.33135  30.96205 1675.110 3.734285  2041393  2619317  2570680
## USA-2000 282.89574 139.29607 1848.147 3.578583  9977582 13511612 13035321
## USA-2002 288.47085 139.08432 1805.477 3.598119 10524779 14027745 13503168
## USA-2004 293.53089 141.63098 1783.413 3.617761 11251801 15090846 14366189
## USA-2006 298.86052 146.61525 1778.528 3.642329 12126527 16170304 15318001
## USA-2008 304.47314 147.52623 1761.316 3.671921 12569281 16125585 15370500
## USA-2010 309.87617 141.34911 1738.001 3.701753 12764841 15842214 15317448
## USA-2012 314.79946 144.86284 1753.699 3.712276 13206454 16505245 15946878
## USA-2014 319.44863 148.46339 1764.597 3.722829 13685949 17113208 16605887
##             cgdpo       ck      ctfp     cwtfp   rgdpna   rconna    rdana
## GBR-2000  2011111  5134820 0.9471037 0.9298179  1849012  1538370  1967642
## GBR-2002  2088659  5185287 0.9554247 0.9469899  1947393  1661618  2105152
## GBR-2004  2162665  5802754 0.9197314 0.9206511  2062448  1782713  2239532
## GBR-2006  2314418  7125918 0.9016753 0.8867161  2180790  1869845  2353489
## GBR-2008  2318905  8470947 0.8398271 0.8557630  2226741  1917020  2383924
## GBR-2010  2190839  9973122 0.7192608 0.7415940  2166256  1877744  2331174
## GBR-2012  2273115 10618961 0.7097169 0.7300584  2235028  1913694  2385488
## GBR-2014  2465456 11811327 0.7187873 0.7358745  2350437  1991213  2526581
## USA-2000 12983206 35997032 1.0000000 1.0000000 12975535 10500206 13647352
## USA-2002 13339370 38467564 1.0000000 1.0000000 13336194 11088529 14123900
## USA-2004 14232334 42071616 1.0000000 1.0000000 14229557 11796878 15181932
## USA-2006 15099868 47891040 1.0000000 1.0000000 15097712 12476968 16121374
## USA-2008 15321926 50006724 1.0000000 1.0000000 15321422 12759836 16086510
## USA-2010 15273702 48876336 1.0000000 1.0000000 15273331 12883714 15924426
## USA-2012 15863845 50020716 1.0000000 1.0000000 15863049 13182059 16509182
## USA-2014 16490883 52849892 1.0000000 1.0000000 16490192 13585164 17137356
##              rkna    rtfpna   rwtfpna     labsh      delta        xr    pl_con
## GBR-2000  8162493 0.9527478 0.9563877 0.6309897 0.04590227 0.6609308 0.7730830
## GBR-2002  8467400 0.9799596 0.9992812 0.6373287 0.04374646 0.6672233 0.7911140
## GBR-2004  8781973 1.0136995 1.0383248 0.6274449 0.04058720 0.5461800 1.0382537
## GBR-2006  9129126 1.0300403 1.0485817 0.6270030 0.03842190 0.5434867 1.1103029
## GBR-2008  9483548 1.0242398 1.0343657 0.6201425 0.03771575 0.5439663 1.1878980
## GBR-2010  9652181 0.9896541 1.0046118 0.6247535 0.03776076 0.6471793 1.1091706
## GBR-2012  9856324 0.9937612 1.0005206 0.6144362 0.03753510 0.6330470 1.1681970
## GBR-2014 10107181 1.0041046 1.0181538 0.6125513 0.03676019 0.6077296 1.2356402
## USA-2000 38439588 0.9205835 0.9289908 0.6426795 0.05212035 1.0000000 0.8255066
## USA-2002 40679832 0.9388351 0.9539754 0.6347357 0.05012728 1.0000000 0.8584893
## USA-2004 43024076 0.9741488 0.9972088 0.6222099 0.04774661 1.0000000 0.9002079
## USA-2006 45671956 0.9863822 1.0105580 0.6123036 0.04556167 1.0000000 0.9395798
## USA-2008 47779436 0.9808996 0.9881262 0.6150548 0.04627780 1.0000000 0.9851168
## USA-2010 48728140 0.9990609 0.9994178 0.5952319 0.04710827 1.0000000 0.9968326
## USA-2012 49960600 1.0051460 1.0036752 0.6020187 0.04788478 1.0000000 1.0294040
## USA-2014 51190644 1.0141082 1.0111778 0.6035975 0.04704589 1.0000000 1.0537966
##              pl_da   pl_gdpo        i_cig      i_xm   i_xr i_outlier cor_exp
## GBR-2000 0.7715102 0.7730696    benchmark benchmark market        no      NA
## GBR-2002 0.7943278 0.8044384    benchmark benchmark market        no      NA
## GBR-2004 1.0292385 1.0625654    benchmark benchmark market        no      NA
## GBR-2006 1.0891278 1.1182685    benchmark benchmark market        no      NA
## GBR-2008 1.1576535 1.2046851    benchmark benchmark market        no      NA
## GBR-2010 1.0542688 1.0971051    benchmark benchmark market        no      NA
## GBR-2012 1.1032517 1.1572107    benchmark benchmark market        no      NA
## GBR-2014 1.1626858 1.2123085    benchmark benchmark market        no      NA
## USA-2000 0.7889932 0.7921603 interpolated benchmark market        no      NA
## USA-2002 0.8129588 0.8229414    benchmark benchmark market        no      NA
## USA-2004 0.8544319 0.8624678 interpolated benchmark market        no      NA
## USA-2006 0.9045495 0.9176166 interpolated benchmark market        no      NA
## USA-2008 0.9575869 0.9606227 interpolated benchmark market        no      NA
## USA-2010 0.9769499 0.9797481 interpolated benchmark market        no      NA
## USA-2012 1.0130669 1.0183694 extrapolated benchmark market        no      NA
## USA-2014 1.0446941 1.0519795 extrapolated benchmark market        no      NA
##          statcap     csh_c     csh_i      csh_g      csh_x      csh_m
## GBR-2000      NA 0.6695670 0.2009486 0.15118961 0.27215350 -0.3255441
## GBR-2002      NA 0.6769798 0.1915792 0.17376177 0.25672942 -0.3210518
## GBR-2004      NA 0.6916623 0.1967494 0.17296985 0.26966739 -0.3673002
## GBR-2006      NA 0.6737601 0.2092361 0.17012757 0.31067675 -0.3984770
## GBR-2008      NA 0.6756253 0.2101049 0.18669203 0.27829620 -0.4001066
## GBR-2010      NA 0.6522532 0.2148008 0.20237352 0.26941344 -0.3967097
## GBR-2012      NA 0.6454995 0.2204630 0.20428941 0.28417677 -0.4131205
## GBR-2014      NA 0.6338343 0.2344086 0.19416399 0.27393726 -0.3789007
## USA-2000      NA 0.6758358 0.2722001 0.09266327 0.10603466 -0.1566473
## USA-2002      NA 0.6889258 0.2626036 0.10007539 0.09348762 -0.1526167
## USA-2004      NA 0.6870325 0.2697411 0.10354772 0.09122263 -0.1587287
## USA-2006      NA 0.6949668 0.2678021 0.10812150 0.10488261 -0.1837855
## USA-2008      NA 0.7019295 0.2321056 0.11841653 0.11299946 -0.1750899
## USA-2010      NA 0.7068287 0.2014818 0.12891109 0.11498131 -0.1603202
## USA-2012      NA 0.7113655 0.2079439 0.12112205 0.12747377 -0.1780486
## USA-2014      NA 0.7167840 0.2078275 0.11312606 0.12769014 -0.1767433
##                csh_r      pl_c      pl_i      pl_g      pl_x      pl_m
## GBR-2000 0.031685416 0.7461854 0.7650863 0.8922034 0.5387948 0.5723231
## GBR-2002 0.022001587 0.7699903 0.8085992 0.8734126 0.5333555 0.5548418
## GBR-2004 0.036251169 0.9895672 0.9896205 1.2329383 0.6087583 0.6330809
## GBR-2006 0.034676518 1.0533600 1.0037246 1.3358153 0.6377970 0.6666489
## GBR-2008 0.049388219 1.1442323 1.0335227 1.3459213 0.7469229 0.7602253
## GBR-2010 0.057868775 1.0874327 0.8358320 1.1792317 0.7149853 0.7221244
## GBR-2012 0.058691852 1.1654679 0.8529153 1.1768202 0.7449705 0.7338502
## GBR-2014 0.042556617 1.2379344 0.9049899 1.2281511 0.7567233 0.7437919
## USA-2000 0.009913484 0.7741043 0.6859053 1.2004077 0.5668258 0.6185908
## USA-2002 0.007524286 0.8035018 0.6761612 1.2370269 0.5558824 0.5905658
## USA-2004 0.007184889 0.8447491 0.7202677 1.2681735 0.6299770 0.6751730
## USA-2006 0.008012477 0.8866088 0.7995001 1.2800587 0.6548091 0.6914976
## USA-2008 0.009638831 0.9310760 0.8602863 1.3054508 0.7507930 0.8069550
## USA-2010 0.008117276 0.9450076 0.8944773 1.2809926 0.7277685 0.7809259
## USA-2012 0.010143337 0.9792322 0.9476624 1.3240701 0.7639757 0.8052509
## USA-2014 0.011315644 1.0038527 1.0083452 1.3702492 0.7692084 0.8049124
##               pl_k
## GBR-2000 0.9000055
## GBR-2002 1.0013583
## GBR-2004 1.2344007
## GBR-2006 1.1702131
## GBR-2008 1.1152974
## GBR-2010 0.8187803
## GBR-2012 0.8415760
## GBR-2014 0.8534581
## USA-2000 0.7926286
## USA-2002 0.8231374
## USA-2004 0.8626361
## USA-2006 0.9177476
## USA-2008 0.9606543
## USA-2010 0.9797719
## USA-2012 1.0184206
## USA-2014 1.0520236

dataframe_3<-funcion_variable_capital_detail_c3(country = c("Mexico","Canada"),anio_inicio_4 = 2000,anio_final_4 = 2014)
print(dataframe_3)

##          country year      ck    rkna      pl_k
## CAN-2001  Canada 2001 3268334 3905941 0.6292847
## CAN-2003  Canada 2003 3349291 4151862 0.7568532
## CAN-2005  Canada 2005 3865556 4462552 0.8875628
## CAN-2007  Canada 2007 4445640 4812567 1.0519462
## CAN-2009  Canada 2009 4794360 5106391 1.0221647
## CAN-2011  Canada 2011 5427466 5427466 1.1579119
## CAN-2013  Canada 2013 5828469 5779532 1.1488672
## MEX-2000  Mexico 2000 2683662 3850000 0.6657988
## MEX-2002  Mexico 2002 2552782 4150159 0.8063704
## MEX-2004  Mexico 2004 3077106 4461555 0.7196133
## MEX-2006  Mexico 2006 3770402 4852529 0.7278860
## MEX-2008  Mexico 2008 4036200 5305337 0.8066145
## MEX-2010  Mexico 2010 5054693 5671746 0.6478299
## MEX-2012  Mexico 2012 6089364 6096434 0.6141177
## MEX-2014  Mexico 2014 6677512 6498114 0.6044782