Script para obtener la proyección de crecimiento tendencial (asumiendo linealidad) a partir del PIB y el IMACEC

pib_imacec.R

# "pib trim.xlsx" es el PIB trimestral a precios encadenados de este enlace:
#https://si3.bcentral.cl/Siete/ES/Siete/Cuadro/CAP_CCNN/MN_CCNN76/CCNN2018_P0_V2/637801082315858005?cbFechaInicio=2000&cbFechaTermino=2024&cbFrecuencia=QUARTERLY&cbCalculo=NONE&cbFechaBase=

pibtrim <- readxl::read_excel("pib trim.xlsx",skip = 1)

colnames(pibtrim) <- c("time", "pib")

pibtrim <- pibtrim %>% 
  mutate(time2 = ymd(str_sub(time, 1, 10))) %>% 
  mutate(rate = log(pib/lag(pib)),
         anio = year(time2))

avg2018 <- pibtrim %>% 
  filter(anio == 2018) %>% 
  pull(pib) %>% 
  mean()

pibtrim$pib18 <- pibtrim$pib/avg2018


# "imacec.xlsx" IMACEC es el mensual desestacionalizado de este enlace:
#https://si3.bcentral.cl/Siete/ES/Siete/Cuadro/CAP_CCNN/MN_CCNN76/CCNN2018_IMACEC_03_A/638131831615238879?cbFechaInicio=2000&cbFechaTermino=2024&cbFrecuencia=MONTHLY&cbCalculo=NONE&cbFechaBase=

imacec <- readxl::read_excel("imacec.xlsx", skip = 1)

colnames(imacec) <- c("time", "imacec_index")

imacec <- imacec %>% 
  mutate(time2 = ymd(str_sub(time, 1, 10))) %>% 
  mutate(trim = quarter(time2),
         anio = year(time2))

imactrim <- imacec %>% 
  group_by(anio, trim) %>% 
  summarise(time = max(time2),
            avgimacec = mean(imacec_index)) %>% 
  as.data.frame()


# PIB POTENCIAL
y1pib <- first(pibtrim$pib18[pibtrim$time2>= as.Date("2015-01-01")])

temp <- pibtrim %>% 
  filter(time2 >= as.Date("2015-01-01"),
         time2 <= as.Date("2019-01-01")) %>% 
  mutate(corre = row_number())

m_pib <- as.numeric(coef(lm(pib18~corre, data = temp))[2])

serie1 <- pibtrim %>% 
  mutate(corte = ifelse(time2 < as.Date("2015-01-01"),
                        0, 1)) %>%
  mutate(periodo = ifelse(
    time2 < as.Date("2015-01-01"),
    corte,
    cumsum(corte)
  )) %>%
  mutate(pibproyectado = ifelse(
    time2 < as.Date("2015-01-01"),
    pib18,
    (m_pib*periodo)+y1pib
  ))

serie1 %>% 
  ggplot() +
  aes(x=time2) +
  geom_line(aes(y = pibproyectado*100, color = "Proyectado"),
            linewidth = 1, linetype = "dashed") +
  geom_line(aes(y = pib18*100, color = "PIB"),
            linewidth = 1.2) +
  scale_x_date(breaks = "1 year",
               expand = c(0,0)) +
  theme(axis.text.x = element_text(angle = 90, vjust = .5),
        axis.title.x = element_blank(),
        axis.title.y = element_blank(),
        legend.title = element_blank(),
        legend.position.inside = c(.2, .8)) +
  labs(title = "PIB trimestral",
       subtitle = "2018 = 100")


# IMACEC POTENCIAL
temp2 <- imacec %>% 
  filter(time2 >= as.Date("2015-01-01"),
         time2 <= as.Date("2019-01-01")) %>% 
  mutate(corre = row_number())

y1ima <- first(imacec$imacec_index[imacec$time2>= as.Date("2015-01-01")])
m_ima <- as.numeric(coef(lm(imacec_index~corre, data = temp2))[2])

serie2 <- imacec %>% 
  mutate(corte = ifelse(time2 < as.Date("2015-01-01"),
                        0, 1)) %>%
  mutate(periodo = ifelse(
    time2 < as.Date("2015-01-01"),
    corte,
    cumsum(corte)
  )) %>%
  mutate(imacecproyectado = ifelse(
    time2 < as.Date("2015-01-01"),
    imacec_index,
    (m_ima*periodo)+y1ima
  ))

serie2 %>% 
  as.data.frame() %>% 
  ggplot() +
  aes(x=time2) +
  geom_line(aes(y = imacecproyectado, color = "Proyectado"),
            linewidth = 1, linetype = "dashed") +
  geom_line(aes(y = imacec_index, color = "IMACEC"),
            linewidth = 1.2) +
  scale_x_date(breaks = "1 year",
               expand = c(0,0)) +
  theme(axis.text.x = element_text(angle = 90, vjust = .5),
        axis.title.x = element_blank(),
        axis.title.y = element_blank(),
        legend.title = element_blank(),
        legend.position = c(.2, .8)) +
  labs(title = "IMACEC mensual",
       subtitle = "Serie desestacionalizada")