PREPARACIÓN DE LOS DATOS

library(readxl)
PIBT_SV <- read_excel(
  "C:/Users/karla/Downloads/datos_PIB_trim_CA.xlsx",
  range = "C7:C144",
  col_types = c("numeric")
)
PIBT_GT <- read_excel(
  "C:/Users/karla/Downloads/datos_PIB_trim_CA.xlsx",
  range = "D51:D144",
  col_types = c("numeric")
)
PIBT_HN <- read_excel(
  "C:/Users/karla/Downloads/datos_PIB_trim_CA.xlsx",
  range = "E47:E144",
  col_types = c("numeric")
)
PIBT_NI <- read_excel(
  "C:/Users/karla/Downloads/datos_PIB_trim_CA.xlsx",
  range = "f71:f144",
  col_types = c("numeric")
)
PIBT_CR <- read_excel(
  "C:/Users/karla/Downloads/datos_PIB_trim_CA.xlsx",
  range = "B11:B144",
  col_types = c("numeric")
)

PIBT_PA <- read_excel(
  "C:/Users/karla/Downloads/datos_PIB_trim_CA.xlsx",
  range = "H31:H137",
  col_types = c("numeric")
)
PIBT_RD <- read_excel(
  "C:/Users/karla/Downloads/datos_PIB_trim_CA.xlsx",
  range = "g11:g144",
  col_types = c("numeric")
)

EL SALVADOR (1990 I - 2024 II) Filtro de Hodrick-Prescott

library(mFilter)
library(forecast)
TS_PIBT_SV <- ts(PIBT_SV, start = c(2006, 1), frequency = 4)
# aplicando el filtro hp y escogiendo el valor de lambda de 1600 dado que es trimestral
hp_SV <- hpfilter(TS_PIBT_SV, freq = 1600)
trend_SV <- hp_SV$trend
cycle_SV <- hp_SV$cycle

Implementación Personalizada

plot(
  TS_PIBT_SV,
  type = "l",
  main = "EL SALVADOR (1990 I - 2024 II) - Filtro de Hodrick-Prescott",
  ylab = "PIB",
  xlab = "Tiempo"
)
lines(trend_SV, col = "green", lwd = 2)
legend(
  "topleft",
  legend = c("PIB Original", "Tendencia (Filtro HP)"),
  col = c("black", "green"),
  lty = 1,
  lwd = 2
)

plot(
  cycle_SV,
  type = "l",
  main = "EL SALVADOR (1990 I - 2024 II) - Componente Ciclico",
  ylab = "Ciclo",
  xlab = "Tiempo"
)

Implementación más rápida del gráfico

plot(hp_SV, ask = FALSE)

GUATEMALA (2001 I - 2024 II) Filtro de Hodrick-Prescott

TS_PIBT_GT <- ts(PIBT_GT, start = c(2006, 1), frequency = 4)
hp_GT <- hpfilter(TS_PIBT_GT, freq = 1600)
trend_GT <- hp_GT$trend
cycle_GT <- hp_GT$cycle

Implementación Personalizada

plot(
 TS_PIBT_GT,
  type = "l",
  main = "GUATEMALA (2001 I - 2024 II) - Filtro de Hodrick-Prescott",
  ylab = "PIB",
  xlab = "Tiempo"
)
lines(trend_GT, col = "green", lwd = 2)
legend(
  "topleft",
  legend = c("PIB Original", "Tendencia (Filtro HP)"),
  col = c("black", "green"),
  lty = 1,
  lwd = 2
)

plot(
  cycle_GT,
  type = "l",
  main = "GUATEMALA (2001 I - 2024 II) - Componente Ciclico",
  ylab = "Ciclo",
  xlab = "Tiempo"
)

Implementación más rápida del gráfico

plot(hp_GT, ask = FALSE)

HONDURAS (2000 I - 2024 II) Filtro de Hodrick-Prescott

TS_PIBT_HN <- ts(PIBT_HN, start = c(2006, 1), frequency = 4)
hp_HN <- hpfilter(TS_PIBT_HN, freq = 1600)
trend_HN <- hp_HN$trend
cycle_HN <- hp_HN$cycle

Implementación Personalizada

plot(
 TS_PIBT_HN,
  type = "l",
  main = "HONDURAS (2000 I - 2024 II) - Filtro de Hodrick-Prescott",
  ylab = "PIB",
  xlab = "Tiempo"
)
lines(trend_HN, col = "green", lwd = 2)
legend(
  "topleft",
  legend = c("PIB Original", "Tendencia (Filtro HP)"),
  col = c("black", "green"),
  lty = 1,
  lwd = 2
)

plot(
  cycle_HN,
  type = "l",
  main = "HONDURAS (2000 I - 2024 II) - Componente Ciclico",
  ylab = "Ciclo",
  xlab = "Tiempo"
)

Implementación más rápida del gráfico

plot(hp_HN, ask = FALSE)

NICARAGUA (2006 I - 2024 II) Filtro de Hodrick-Prescott

TS_PIBT_NI <- ts(PIBT_NI, start = c(2006, 1), frequency = 4)
hp_NI <- hpfilter(TS_PIBT_NI, freq = 1600)
trend_NI <- hp_NI$trend
cycle_NI <- hp_NI$cycle

Implementación Personalizada

plot(
 TS_PIBT_NI,
  type = "l",
  main = "NICARAGUA (2006 I - 2024 II) - Filtro de Hodrick-Prescott",
  ylab = "PIB",
  xlab = "Tiempo"
)
lines(trend_NI, col = "green", lwd = 2)
legend(
  "topleft",
  legend = c("PIB Original", "Tendencia (Filtro HP)"),
  col = c("black", "green"),
  lty = 1,
  lwd = 2
)

plot(
  cycle_NI,
  type = "l",
  main = "NICARAGUA (2006 I - 2024 II) - Componente Ciclico",
  ylab = "Ciclo",
  xlab = "Tiempo"
)

Implementación más rápida del gráfico

plot(hp_NI, ask = FALSE)

COSTA RICA (1991 I - 2024 II) Filtro de Hodrick-Prescott

TS_PIBT_CR <- ts(PIBT_CR, start = c(2006, 1), frequency = 4)
hp_CR <- hpfilter(TS_PIBT_CR, freq = 1600)
trend_CR <- hp_CR$trend
cycle_CR <- hp_CR$cycle

Implementación Personalizada

plot(
 TS_PIBT_CR,
  type = "l",
  main = "COSTA RICA (1991 I - 2024 II) - Filtro de Hodrick-Prescott",
  ylab = "PIB",
  xlab = "Tiempo"
)
lines(trend_CR, col = "green", lwd = 2)
legend(
  "topleft",
  legend = c("PIB Original", "Tendencia (Filtro HP)"),
  col = c("black", "green"),
  lty = 1,
  lwd = 2
)

plot(
  cycle_CR,
  type = "l",
  main = "COSTA RICA (1991 I - 2024 II) - Componente Ciclico",
  ylab = "Ciclo",
  xlab = "Tiempo"
)

Implementación más rápida del gráfico

plot(hp_CR, ask = FALSE)

PANAMÁ (1996 I - 2022 III) Filtro de Hodrick-Prescott

TS_PIBT_PA <- ts(PIBT_PA, start = c(2006, 1), frequency = 4)
hp_PA <- hpfilter(TS_PIBT_PA, freq = 1600)
trend_PA <- hp_PA$trend
cycle_PA <- hp_PA$cycle

Implementación Personalizada

plot(
 TS_PIBT_PA,
  type = "l",
  main = "PANAMÁ (1996 I - 2022 III) - Filtro de Hodrick-Prescott",
  ylab = "PIB",
  xlab = "Tiempo"
)
lines(trend_PA, col = "green", lwd = 2)
legend(
  "topleft",
  legend = c("PIB Original", "Tendencia (Filtro HP)"),
  col = c("black", "green"),
  lty = 1,
  lwd = 2
)

plot(
  cycle_PA,
  type = "l",
  main = "COSTA RICA (1991 I - 2024 II) - Componente Ciclico",
  ylab = "Ciclo",
  xlab = "Tiempo"
)

Implementación más rápida del gráfico

plot(hp_PA, ask = FALSE)

REPÚBLICA DOMINICANA (1991 I - 2024 II) Filtro de Hodrick-Prescott

TS_PIBT_RD <- ts(PIBT_RD, start = c(2006, 1), frequency = 4)
hp_RD <- hpfilter(TS_PIBT_RD, freq = 1600)
trend_RD <- hp_RD$trend
cycle_RD <- hp_RD$cycle

Implementación Personalizada

plot(
 TS_PIBT_RD,
  type = "l",
  main = "REPÚBLICA DOMINICANA (1991 I - 2024 II) - Filtro de Hodrick-Prescott",
  ylab = "PIB",
  xlab = "Tiempo"
)
lines(trend_RD, col = "green", lwd = 2)
legend(
  "topleft",
  legend = c("PIB Original", "Tendencia (Filtro HP)"),
  col = c("black", "green"),
  lty = 1,
  lwd = 2
)

plot(
  cycle_RD,
  type = "l",
  main = "REPÚBLICA DOMINICANA (1991 I - 2024 II) - Componente Ciclico",
  ylab = "Ciclo",
  xlab = "Tiempo"
)

Implementación más rápida del gráfico

plot(hp_RD, ask = FALSE)