MacroGrowth: Economics Models

## ----setup, include = FALSE----------------------------------------------
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>"
)
library(dplyr)
library(ggplot2)
library(magrittr)
library(rlang)
library(tidyr)
library(MacroGrowth)

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library(dplyr)
library(ggplot2)
library(magrittr)
library(rlang)
library(tidyr)
library(MacroGrowth)
head(EconUK)

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sffit <- sfModel(formula = iGDP ~ iK + iYear, data = EconUK)
sffit

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naturalCoef(sffit)

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cdfit <- cdModel(formula = iGDP ~ iK + iL + iYear, data = EconUK)
cdfit

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naturalCoef(cdfit)

## ------------------------------------------------------------------------
cesfit <- cesModel(formula = iGDP ~ iK + iL + iYear, data = EconUK)
naturalCoef(cesfit)

## ------------------------------------------------------------------------
linexfit <- linexModel(formula = iGDP ~ iK + iL + iXp + iYear, data = EconUK)
naturalCoef(linexfit)

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head(fortify(linexfit))

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head(getData(cdfit))

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yhat(cdfit)

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resid(cdfit)

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sum(resid(cdfit)^2)

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sfModel(formula = iGDP ~ iK + iYear, data = EconUK) %>% naturalCoef()
sfModel(formula = iGDP ~ iK + iYear, data = EconUK, constrained = TRUE) %>% naturalCoef()

## ------------------------------------------------------------------------
cdModel(formula = iGDP ~ iK + iL + iXu + iYear, 
        data = EconUK %>% filter(Year < 1970), 
        constrained = FALSE) %>% 
  naturalCoef()

## ------------------------------------------------------------------------
cdModel(formula = iGDP ~ iK + iL + iXu + iYear, data = EconUK %>% filter(Year < 1970)) %>% naturalCoef()

## ------------------------------------------------------------------------
cesModel(formula = iGDP ~ iK + iXu + iYear, 
         data = EconUK %>% filter(Year >= 1980 & Year < 1990), 
         constrained = FALSE) %>% 
  naturalCoef()

## ------------------------------------------------------------------------
cesModel(formula = iGDP ~ iK + iXu + iYear, 
         data = EconUK %>% filter(Year >= 1980 & Year < 1990)) %>% 
  naturalCoef()

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attr(cesfit, "model.attempts")[[1]] %>% naturalCoef()

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cdfits_rs <- resampledFits(model = cdfit, method = "wild", n = 5, seed = 123)

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cdfits_rs$coeffs

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# Original fit
cdfits_rs$models[[1]] %>% naturalCoef()
# First resampled model
cdfits_rs$models[[2]] %>% naturalCoef()
# Last resampled model
cdfits_rs$models[[6]] %>% naturalCoef()

## ------------------------------------------------------------------------
resampledFits(model = sffit, method = "wild", n = 5)[["coeffs"]]
resampledFits(model = cesfit, method = "wild", n = 5)[["coeffs"]]
resampledFits(model = linexfit, method = "wild", n = 5)[["coeffs"]]

## ---- plotting1, fig.width = 6, fig.retina = 2, fig.align = "center"-----
bind_cols(EconUK, yhat(cdfit) %>% as.data.frame() %>% set_names("yhat")) %>% 
  ggplot() + 
  # Add historical data as points
  geom_point(mapping = aes(x = Year, y = iGDP), shape = 1) +
  # Add the fitted model as a line
  geom_line(mapping = aes(x = Year, y = yhat))

## ---- fig.width = 4, fig.height = 3, fig.retina = 2, fig.align = "center"----
triData <- cdModel(formula = iGDP ~ iK + iL + iXu + iYear, data = EconUK) %>%
  resampledFits(method = "wild", n = 100, seed = 123) %>%
  extract2("coeffs")

triData %>% filter(method == "wild") %>% 
  triPlot(mapping = aes(x = alpha_1, y = alpha_2, z = alpha_3), 
          alpha = 0.3) +
  geom_point(data = triData %>% filter(method == "orig"),
             mapping = aes(x = alpha_1, y = alpha_2, z = alpha_3),
             color = "red", alpha = 1, size = 3, stat = "triangle")